model: fix issues with spm tokenizer for Gemma 3 (#10081)

The sliding window cache trims entries that are outside the window for
the latest token. This works when we are extending the cache, such as
when the conversation continues. However, if we have a partial overlap
in conversation (including the BOS tokens), then we resume from a past
point in the conversation and the needed tokens are no longer stored
in memory. This verifies that the new window overlaps with the old one
before reusing the cache.

Co-authored-by: Jesse Gross <jesse@ollama.com>

CMakeLists.txt

@@ -86,9 +86,9 @@ if(CMAKE_CUDA_COMPILER)
     )
 endif()
 
-set(WINDOWS_AMDGPU_TARGETS_EXCLUDE_REGEX "^gfx(906|908|90a):xnack[+-]$"
+set(WINDOWS_AMDGPU_TARGETS_EXCLUDE_REGEX "^gfx(906|908|90a|1200|1201):xnack[+-]$"
     CACHE STRING
-    "Regular expression describing AMDGPU_TARGETS not supported on Windows. Override to force building these targets. Default \"^gfx(906|908|90a):xnack[+-]$\"."
+    "Regular expression describing AMDGPU_TARGETS not supported on Windows. Override to force building these targets. Default \"^gfx(906|908|90a|1200|1201):xnack[+-]$\"."
 )
 
 check_language(HIP)
@@ -97,7 +97,7 @@ if(CMAKE_HIP_COMPILER)
 
     find_package(hip REQUIRED)
     if(NOT AMDGPU_TARGETS)
-        list(FILTER AMDGPU_TARGETS INCLUDE REGEX "^gfx(900|94[012]|101[02]|1030|110[012])$")
+        list(FILTER AMDGPU_TARGETS INCLUDE REGEX "^gfx(900|94[012]|101[02]|1030|110[012]|120[01])$")
     elseif(WIN32 AND WINDOWS_AMDGPU_TARGETS_EXCLUDE_REGEX)
         list(FILTER AMDGPU_TARGETS EXCLUDE REGEX ${WINDOWS_AMDGPU_TARGETS_EXCLUDE_REGEX})
     endif()

CMakePresets.json

@@ -56,7 +56,7 @@
       "name": "ROCm 6",
       "inherits": [ "ROCm" ],
       "cacheVariables": {
-        "AMDGPU_TARGETS": "gfx900;gfx940;gfx941;gfx942;gfx1010;gfx1012;gfx1030;gfx1100;gfx1101;gfx1102;gfx906:xnack-;gfx908:xnack-;gfx90a:xnack+;gfx90a:xnack-"
+        "AMDGPU_TARGETS": "gfx900;gfx940;gfx941;gfx942;gfx1010;gfx1012;gfx1030;gfx1100;gfx1101;gfx1102;gfx1151;gfx1200;gfx1201;gfx906:xnack-;gfx908:xnack-;gfx90a:xnack+;gfx90a:xnack-"
       }
     }
   ],

README.md

@@ -285,6 +285,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [Bionic GPT](https://github.com/bionic-gpt/bionic-gpt)
 - [HTML UI](https://github.com/rtcfirefly/ollama-ui)
 - [Saddle](https://github.com/jikkuatwork/saddle)
+- [TagSpaces](https://www.tagspaces.org) (A platform for file based apps, [utilizing Ollama](https://docs.tagspaces.org/ai/) for the generation of tags and descriptions)
 - [Chatbot UI](https://github.com/ivanfioravanti/chatbot-ollama)
 - [Chatbot UI v2](https://github.com/mckaywrigley/chatbot-ui)
 - [Typescript UI](https://github.com/ollama-interface/Ollama-Gui?tab=readme-ov-file)
@@ -324,6 +325,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [RWKV-Runner](https://github.com/josStorer/RWKV-Runner) (RWKV offline LLM deployment tool, also usable as a client for ChatGPT and Ollama)
 - [Ollama Grid Search](https://github.com/dezoito/ollama-grid-search) (app to evaluate and compare models)
 - [Olpaka](https://github.com/Otacon/olpaka) (User-friendly Flutter Web App for Ollama)
+- [Casibase](https://casibase.org) (An open source AI knowledge base and dialogue system combining the latest RAG, SSO, ollama support and multiple large language models.)
 - [OllamaSpring](https://github.com/CrazyNeil/OllamaSpring) (Ollama Client for macOS)
 - [LLocal.in](https://github.com/kartikm7/llocal) (Easy to use Electron Desktop Client for Ollama)
 - [Shinkai Desktop](https://github.com/dcSpark/shinkai-apps) (Two click install Local AI using Ollama + Files + RAG)
@@ -392,6 +394,10 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [1Panel](https://github.com/1Panel-dev/1Panel/) (Web-based Linux Server Management Tool)
 - [AstrBot](https://github.com/Soulter/AstrBot/) (User-friendly LLM-based multi-platform chatbot with a WebUI, supporting RAG, LLM agents, and plugins integration)
 - [Reins](https://github.com/ibrahimcetin/reins) (Easily tweak parameters, customize system prompts per chat, and enhance your AI experiments with reasoning model support.)
+- [Ellama](https://github.com/zeozeozeo/ellama) (Friendly native app to chat with an Ollama instance)
+- [screenpipe](https://github.com/mediar-ai/screenpipe) Build agents powered by your screen history
+- [Ollamb](https://github.com/hengkysteen/ollamb) (Simple yet rich in features, cross-platform built with Flutter and designed for Ollama. Try the [web demo](https://hengkysteen.github.io/demo/ollamb/).)
+- [Writeopia](https://github.com/Writeopia/Writeopia) (Text editor with integration with Ollama)
 
 ### Cloud
 
@@ -431,7 +437,9 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [SwollamaCLI](https://github.com/marcusziade/Swollama) bundled with the Swollama Swift package. [Demo](https://github.com/marcusziade/Swollama?tab=readme-ov-file#cli-usage)
 - [aichat](https://github.com/sigoden/aichat) All-in-one LLM CLI tool featuring Shell Assistant, Chat-REPL, RAG, AI tools & agents, with access to OpenAI, Claude, Gemini, Ollama, Groq, and more.
 - [PowershAI](https://github.com/rrg92/powershai) PowerShell module that brings AI to terminal on Windows, including support for Ollama
+- [DeepShell](https://github.com/Abyss-c0re/deepshell) Your self-hosted AI assistant. Interactive Shell, Files and Folders analysis.
 - [orbiton](https://github.com/xyproto/orbiton) Configuration-free text editor and IDE with support for tab completion with Ollama.
+- [orca-cli](https://github.com/molbal/orca-cli) Ollama Registry CLI Application - Browse, pull and download models from Ollama Registry in your terminal.
 
 ### Apple Vision Pro
 
@@ -510,6 +518,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [Ollama for Zig](https://github.com/dravenk/ollama-zig)
 - [Abso](https://github.com/lunary-ai/abso) (OpenAI-compatible TypeScript SDK for any LLM provider)
 - [Nichey](https://github.com/goodreasonai/nichey) is a Python package for generating custom wikis for your research topic
+- [Ollama for D](https://github.com/kassane/ollama-d)
 
 ### Mobile
 

api/types.go

@@ -12,6 +12,7 @@ import (
 	"time"
 
 	"github.com/ollama/ollama/envconfig"
+	"github.com/ollama/ollama/types/model"
 )
 
 // StatusError is an error with an HTTP status code and message.
@@ -81,7 +82,7 @@ type GenerateRequest struct {
 
 	// Options lists model-specific options. For example, temperature can be
 	// set through this field, if the model supports it.
-	Options map[string]interface{} `json:"options"`
+	Options map[string]any `json:"options"`
 }
 
 // ChatRequest describes a request sent by [Client.Chat].
@@ -106,7 +107,7 @@ type ChatRequest struct {
 	Tools `json:"tools,omitempty"`
 
 	// Options lists model-specific options.
-	Options map[string]interface{} `json:"options"`
+	Options map[string]any `json:"options"`
 }
 
 type Tools []Tool
@@ -260,7 +261,7 @@ type EmbedRequest struct {
 	Truncate *bool `json:"truncate,omitempty"`
 
 	// Options lists model-specific options.
-	Options map[string]interface{} `json:"options"`
+	Options map[string]any `json:"options"`
 }
 
 // EmbedResponse is the response from [Client.Embed].
@@ -286,7 +287,7 @@ type EmbeddingRequest struct {
 	KeepAlive *Duration `json:"keep_alive,omitempty"`
 
 	// Options lists model-specific options.
-	Options map[string]interface{} `json:"options"`
+	Options map[string]any `json:"options"`
 }
 
 // EmbeddingResponse is the response from [Client.Embeddings].
@@ -332,7 +333,7 @@ type ShowRequest struct {
 	Template string `json:"template"`
 	Verbose  bool   `json:"verbose"`
 
-	Options map[string]interface{} `json:"options"`
+	Options map[string]any `json:"options"`
 
 	// Deprecated: set the model name with Model instead
 	Name string `json:"name"`
@@ -340,17 +341,18 @@ type ShowRequest struct {
 
 // ShowResponse is the response returned from [Client.Show].
 type ShowResponse struct {
-	License       string         `json:"license,omitempty"`
-	Modelfile     string         `json:"modelfile,omitempty"`
-	Parameters    string         `json:"parameters,omitempty"`
-	Template      string         `json:"template,omitempty"`
-	System        string         `json:"system,omitempty"`
-	Details       ModelDetails   `json:"details,omitempty"`
-	Messages      []Message      `json:"messages,omitempty"`
-	ModelInfo     map[string]any `json:"model_info,omitempty"`
-	ProjectorInfo map[string]any `json:"projector_info,omitempty"`
-	Tensors       []Tensor       `json:"tensors,omitempty"`
-	ModifiedAt    time.Time      `json:"modified_at,omitempty"`
+	License       string             `json:"license,omitempty"`
+	Modelfile     string             `json:"modelfile,omitempty"`
+	Parameters    string             `json:"parameters,omitempty"`
+	Template      string             `json:"template,omitempty"`
+	System        string             `json:"system,omitempty"`
+	Details       ModelDetails       `json:"details,omitempty"`
+	Messages      []Message          `json:"messages,omitempty"`
+	ModelInfo     map[string]any     `json:"model_info,omitempty"`
+	ProjectorInfo map[string]any     `json:"projector_info,omitempty"`
+	Tensors       []Tensor           `json:"tensors,omitempty"`
+	Capabilities  []model.Capability `json:"capabilities,omitempty"`
+	ModifiedAt    time.Time          `json:"modified_at,omitempty"`
 }
 
 // CopyRequest is the request passed to [Client.Copy].
@@ -503,7 +505,7 @@ func (m *Metrics) Summary() {
 	}
 }
 
-func (opts *Options) FromMap(m map[string]interface{}) error {
+func (opts *Options) FromMap(m map[string]any) error {
 	valueOpts := reflect.ValueOf(opts).Elem() // names of the fields in the options struct
 	typeOpts := reflect.TypeOf(opts).Elem()   // types of the fields in the options struct
 
@@ -560,12 +562,12 @@ func (opts *Options) FromMap(m map[string]interface{}) error {
 				}
 				field.SetString(val)
 			case reflect.Slice:
-				// JSON unmarshals to []interface{}, not []string
-				val, ok := val.([]interface{})
+				// JSON unmarshals to []any, not []string
+				val, ok := val.([]any)
 				if !ok {
 					return fmt.Errorf("option %q must be of type array", key)
 				}
-				// convert []interface{} to []string
+				// convert []any to []string
 				slice := make([]string, len(val))
 				for i, item := range val {
 					str, ok := item.(string)
@@ -672,7 +674,7 @@ func (d *Duration) UnmarshalJSON(b []byte) (err error) {
 }
 
 // FormatParams converts specified parameter options to their correct types
-func FormatParams(params map[string][]string) (map[string]interface{}, error) {
+func FormatParams(params map[string][]string) (map[string]any, error) {
 	opts := Options{}
 	valueOpts := reflect.ValueOf(&opts).Elem() // names of the fields in the options struct
 	typeOpts := reflect.TypeOf(opts)           // types of the fields in the options struct
@@ -686,7 +688,7 @@ func FormatParams(params map[string][]string) (map[string]interface{}, error) {
 		}
 	}
 
-	out := make(map[string]interface{})
+	out := make(map[string]any)
 	// iterate params and set values based on json struct tags
 	for key, vals := range params {
 		if opt, ok := jsonOpts[key]; !ok {

api/types_test.go

@@ -134,7 +134,7 @@ func TestUseMmapParsingFromJSON(t *testing.T) {
 
 	for _, test := range tests {
 		t.Run(test.name, func(t *testing.T) {
-			var oMap map[string]interface{}
+			var oMap map[string]any
 			err := json.Unmarshal([]byte(test.req), &oMap)
 			require.NoError(t, err)
 			opts := DefaultOptions()

benchmark/server_benchmark_test.go

@@ -0,0 +1,178 @@
+package benchmark
+
+import (
+	"context"
+	"flag"
+	"fmt"
+	"testing"
+	"time"
+
+	"github.com/ollama/ollama/api"
+)
+
+// Command line flags
+var modelFlag string
+
+func init() {
+	flag.StringVar(&modelFlag, "m", "", "Name of the model to benchmark")
+	flag.Lookup("m").DefValue = "model"
+}
+
+// modelName returns the model name from flags, failing the test if not set
+func modelName(b *testing.B) string {
+	if modelFlag == "" {
+		b.Fatal("Error: -m flag is required for benchmark tests")
+	}
+	return modelFlag
+}
+
+type TestCase struct {
+	name      string
+	prompt    string
+	maxTokens int
+}
+
+// runGenerateBenchmark contains the common generate and metrics logic
+func runGenerateBenchmark(b *testing.B, ctx context.Context, client *api.Client, req *api.GenerateRequest) {
+	start := time.Now()
+	var ttft time.Duration
+	var metrics api.Metrics
+
+	err := client.Generate(ctx, req, func(resp api.GenerateResponse) error {
+		if ttft == 0 && resp.Response != "" {
+			ttft = time.Since(start)
+		}
+		if resp.Done {
+			metrics = resp.Metrics
+		}
+		return nil
+	})
+
+	// Report custom metrics as part of the benchmark results
+	b.ReportMetric(float64(ttft.Milliseconds()), "ttft_ms")
+	b.ReportMetric(float64(metrics.LoadDuration.Milliseconds()), "load_ms")
+
+	// Token throughput metrics
+	promptThroughput := float64(metrics.PromptEvalCount) / metrics.PromptEvalDuration.Seconds()
+	genThroughput := float64(metrics.EvalCount) / metrics.EvalDuration.Seconds()
+	b.ReportMetric(promptThroughput, "prompt_tok/s")
+	b.ReportMetric(genThroughput, "gen_tok/s")
+
+	// Token counts
+	b.ReportMetric(float64(metrics.PromptEvalCount), "prompt_tokens")
+	b.ReportMetric(float64(metrics.EvalCount), "gen_tokens")
+	if err != nil {
+		b.Fatal(err)
+	}
+}
+
+// BenchmarkColdStart runs benchmarks with model loading from cold state
+func BenchmarkColdStart(b *testing.B) {
+	client := setup(b)
+	tests := []TestCase{
+		{"short_prompt", "Write a long story", 100},
+		{"medium_prompt", "Write a detailed economic analysis", 500},
+		{"long_prompt", "Write a comprehensive AI research paper", 1000},
+	}
+	m := modelName(b)
+
+	for _, tt := range tests {
+		b.Run(fmt.Sprintf("%s/cold/%s", m, tt.name), func(b *testing.B) {
+			ctx := context.Background()
+
+			// Set number of tokens as our throughput metric
+			b.SetBytes(int64(tt.maxTokens))
+
+			for b.Loop() {
+				b.StopTimer()
+				// Ensure model is unloaded before each iteration
+				unload(client, m, b)
+				b.StartTimer()
+
+				req := &api.GenerateRequest{
+					Model:   m,
+					Prompt:  tt.prompt,
+					Options: map[string]any{"num_predict": tt.maxTokens, "temperature": 0.1},
+				}
+
+				runGenerateBenchmark(b, ctx, client, req)
+			}
+		})
+	}
+}
+
+// BenchmarkWarmStart runs benchmarks with pre-loaded model
+func BenchmarkWarmStart(b *testing.B) {
+	client := setup(b)
+	tests := []TestCase{
+		{"short_prompt", "Write a long story", 100},
+		{"medium_prompt", "Write a detailed economic analysis", 500},
+		{"long_prompt", "Write a comprehensive AI research paper", 1000},
+	}
+	m := modelName(b)
+
+	for _, tt := range tests {
+		b.Run(fmt.Sprintf("%s/warm/%s", m, tt.name), func(b *testing.B) {
+			ctx := context.Background()
+
+			// Pre-warm the model
+			warmup(client, m, tt.prompt, b)
+
+			// Set number of tokens as our throughput metric
+			b.SetBytes(int64(tt.maxTokens))
+
+			for b.Loop() {
+				req := &api.GenerateRequest{
+					Model:   m,
+					Prompt:  tt.prompt,
+					Options: map[string]any{"num_predict": tt.maxTokens, "temperature": 0.1},
+				}
+
+				runGenerateBenchmark(b, ctx, client, req)
+			}
+		})
+	}
+}
+
+// setup verifies server and model availability
+func setup(b *testing.B) *api.Client {
+	client, err := api.ClientFromEnvironment()
+	if err != nil {
+		b.Fatal(err)
+	}
+	if _, err := client.Show(context.Background(), &api.ShowRequest{Model: modelName(b)}); err != nil {
+		b.Fatalf("Model unavailable: %v", err)
+	}
+
+	return client
+}
+
+// warmup ensures the model is loaded and warmed up
+func warmup(client *api.Client, model string, prompt string, b *testing.B) {
+	for range 3 {
+		err := client.Generate(
+			context.Background(),
+			&api.GenerateRequest{
+				Model:   model,
+				Prompt:  prompt,
+				Options: map[string]any{"num_predict": 50, "temperature": 0.1},
+			},
+			func(api.GenerateResponse) error { return nil },
+		)
+		if err != nil {
+			b.Logf("Error during model warm-up: %v", err)
+		}
+	}
+}
+
+// unload forces model unloading using KeepAlive: 0 parameter
+func unload(client *api.Client, model string, b *testing.B) {
+	req := &api.GenerateRequest{
+		Model:     model,
+		KeepAlive: &api.Duration{Duration: 0},
+	}
+	if err := client.Generate(context.Background(), req, func(api.GenerateResponse) error { return nil }); err != nil {
+		b.Logf("Unload error: %v", err)
+	}
+	time.Sleep(1 * time.Second)
+}

cmd/cmd.go

@@ -18,6 +18,7 @@ import (
 	"os/signal"
 	"path/filepath"
 	"runtime"
+	"slices"
 	"sort"
 	"strconv"
 	"strings"
@@ -267,7 +268,7 @@ func RunHandler(cmd *cobra.Command, args []string) error {
 	opts := runOptions{
 		Model:    args[0],
 		WordWrap: os.Getenv("TERM") == "xterm-256color",
-		Options:  map[string]interface{}{},
+		Options:  map[string]any{},
 	}
 
 	format, err := cmd.Flags().GetString("format")
@@ -339,6 +340,11 @@ func RunHandler(cmd *cobra.Command, args []string) error {
 		return err
 	}
 
+	opts.MultiModal = slices.Contains(info.Capabilities, model.CapabilityVision)
+
+	// TODO: remove the projector info and vision info checks below,
+	// these are left in for backwards compatibility with older servers
+	// that don't have the capabilities field in the model info
 	if len(info.ProjectorInfo) != 0 {
 		opts.MultiModal = true
 	}
@@ -669,6 +675,15 @@ func showInfo(resp *api.ShowResponse, verbose bool, w io.Writer) error {
 		return
 	})
 
+	if len(resp.Capabilities) > 0 {
+		tableRender("Capabilities", func() (rows [][]string) {
+			for _, capability := range resp.Capabilities {
+				rows = append(rows, []string{"", capability.String()})
+			}
+			return
+		})
+	}
+
 	if resp.ProjectorInfo != nil {
 		tableRender("Projector", func() (rows [][]string) {
 			arch := resp.ProjectorInfo["general.architecture"].(string)
@@ -703,6 +718,8 @@ func showInfo(resp *api.ShowResponse, verbose bool, w io.Writer) error {
 			for _, k := range keys {
 				var v string
 				switch vData := resp.ModelInfo[k].(type) {
+				case bool:
+					v = fmt.Sprintf("%t", vData)
 				case string:
 					v = vData
 				case float64:
@@ -835,7 +852,7 @@ type runOptions struct {
 	Format      string
 	System      string
 	Images      []api.ImageData
-	Options     map[string]interface{}
+	Options     map[string]any
 	MultiModal  bool
 	KeepAlive   *api.Duration
 }

cmd/cmd_test.go

@@ -16,6 +16,7 @@ import (
 	"github.com/spf13/cobra"
 
 	"github.com/ollama/ollama/api"
+	"github.com/ollama/ollama/types/model"
 )
 
 func TestShowInfo(t *testing.T) {
@@ -87,6 +88,8 @@ func TestShowInfo(t *testing.T) {
 			ModelInfo: map[string]any{
 				"general.architecture":    "test",
 				"general.parameter_count": float64(8_000_000_000),
+				"some.true_bool":          true,
+				"some.false_bool":         false,
 				"test.context_length":     float64(1000),
 				"test.embedding_length":   float64(11434),
 			},
@@ -111,6 +114,8 @@ func TestShowInfo(t *testing.T) {
   Metadata
     general.architecture       test     
     general.parameter_count    8e+09    
+    some.false_bool            false    
+    some.true_bool             true     
     test.context_length        1000     
     test.embedding_length      11434    
 
@@ -256,6 +261,34 @@ Weigh anchor!
 			t.Errorf("unexpected output (-want +got):\n%s", diff)
 		}
 	})
+
+	t.Run("capabilities", func(t *testing.T) {
+		var b bytes.Buffer
+		if err := showInfo(&api.ShowResponse{
+			Details: api.ModelDetails{
+				Family:            "test",
+				ParameterSize:     "7B",
+				QuantizationLevel: "FP16",
+			},
+			Capabilities: []model.Capability{model.CapabilityVision, model.CapabilityTools},
+		}, false, &b); err != nil {
+			t.Fatal(err)
+		}
+
+		expect := "  Model\n" +
+			"    architecture    test    \n" +
+			"    parameters      7B      \n" +
+			"    quantization    FP16    \n" +
+			"\n" +
+			"  Capabilities\n" +
+			"    vision    \n" +
+			"    tools     \n" +
+			"\n"
+
+		if diff := cmp.Diff(expect, b.String()); diff != "" {
+			t.Errorf("unexpected output (-want +got):\n%s", diff)
+		}
+	})
 }
 
 func TestDeleteHandler(t *testing.T) {
@@ -757,3 +790,132 @@ func TestCreateHandler(t *testing.T) {
 		})
 	}
 }
+
+func TestNewCreateRequest(t *testing.T) {
+	tests := []struct {
+		name     string
+		from     string
+		opts     runOptions
+		expected *api.CreateRequest
+	}{
+		{
+			"basic test",
+			"newmodel",
+			runOptions{
+				Model:       "mymodel",
+				ParentModel: "",
+				Prompt:      "You are a fun AI agent",
+				Messages:    []api.Message{},
+				WordWrap:    true,
+			},
+			&api.CreateRequest{
+				From:  "mymodel",
+				Model: "newmodel",
+			},
+		},
+		{
+			"parent model test",
+			"newmodel",
+			runOptions{
+				Model:       "mymodel",
+				ParentModel: "parentmodel",
+				Messages:    []api.Message{},
+				WordWrap:    true,
+			},
+			&api.CreateRequest{
+				From:  "parentmodel",
+				Model: "newmodel",
+			},
+		},
+		{
+			"parent model as filepath test",
+			"newmodel",
+			runOptions{
+				Model:       "mymodel",
+				ParentModel: "/some/file/like/etc/passwd",
+				Messages:    []api.Message{},
+				WordWrap:    true,
+			},
+			&api.CreateRequest{
+				From:  "mymodel",
+				Model: "newmodel",
+			},
+		},
+		{
+			"parent model as windows filepath test",
+			"newmodel",
+			runOptions{
+				Model:       "mymodel",
+				ParentModel: "D:\\some\\file\\like\\etc\\passwd",
+				Messages:    []api.Message{},
+				WordWrap:    true,
+			},
+			&api.CreateRequest{
+				From:  "mymodel",
+				Model: "newmodel",
+			},
+		},
+		{
+			"options test",
+			"newmodel",
+			runOptions{
+				Model:       "mymodel",
+				ParentModel: "parentmodel",
+				Options: map[string]any{
+					"temperature": 1.0,
+				},
+			},
+			&api.CreateRequest{
+				From:  "parentmodel",
+				Model: "newmodel",
+				Parameters: map[string]any{
+					"temperature": 1.0,
+				},
+			},
+		},
+		{
+			"messages test",
+			"newmodel",
+			runOptions{
+				Model:       "mymodel",
+				ParentModel: "parentmodel",
+				System:      "You are a fun AI agent",
+				Messages: []api.Message{
+					{
+						Role:    "user",
+						Content: "hello there!",
+					},
+					{
+						Role:    "assistant",
+						Content: "hello to you!",
+					},
+				},
+				WordWrap: true,
+			},
+			&api.CreateRequest{
+				From:   "parentmodel",
+				Model:  "newmodel",
+				System: "You are a fun AI agent",
+				Messages: []api.Message{
+					{
+						Role:    "user",
+						Content: "hello there!",
+					},
+					{
+						Role:    "assistant",
+						Content: "hello to you!",
+					},
+				},
+			},
+		},
+	}
+
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			actual := NewCreateRequest(tt.from, tt.opts)
+			if !cmp.Equal(actual, tt.expected) {
+				t.Errorf("expected output %#v, got %#v", tt.expected, actual)
+			}
+		})
+	}
+}

cmd/interactive.go

@@ -18,6 +18,7 @@ import (
 	"github.com/ollama/ollama/envconfig"
 	"github.com/ollama/ollama/readline"
 	"github.com/ollama/ollama/types/errtypes"
+	"github.com/ollama/ollama/types/model"
 )
 
 type MultilineState int
@@ -459,9 +460,16 @@ func generateInteractive(cmd *cobra.Command, opts runOptions) error {
 }
 
 func NewCreateRequest(name string, opts runOptions) *api.CreateRequest {
+	parentModel := opts.ParentModel
+
+	modelName := model.ParseName(parentModel)
+	if !modelName.IsValid() {
+		parentModel = ""
+	}
+
 	req := &api.CreateRequest{
-		Name: name,
-		From: cmp.Or(opts.ParentModel, opts.Model),
+		Model: name,
+		From:  cmp.Or(parentModel, opts.Model),
 	}
 
 	if opts.System != "" {

convert/convert.go

@@ -201,7 +201,7 @@ func ConvertModel(fsys fs.FS, ws io.WriteSeeker) error {
 	case "CohereForCausalLM":
 		conv = &commandrModel{}
 	default:
-		return errors.New("unsupported architecture")
+		return fmt.Errorf("unsupported architecture %q", p.Architectures[0])
 	}
 
 	if err := json.Unmarshal(bts, conv); err != nil {

convert/sentencepiece/sentencepiece_model.pb.go

@@ -1360,7 +1360,7 @@ func file_sentencepiece_model_proto_rawDescGZIP() []byte {
 
 var file_sentencepiece_model_proto_enumTypes = make([]protoimpl.EnumInfo, 2)
 var file_sentencepiece_model_proto_msgTypes = make([]protoimpl.MessageInfo, 6)
-var file_sentencepiece_model_proto_goTypes = []interface{}{
+var file_sentencepiece_model_proto_goTypes = []any{
 	(TrainerSpec_ModelType)(0),         // 0: sentencepiece.TrainerSpec.ModelType
 	(ModelProto_SentencePiece_Type)(0), // 1: sentencepiece.ModelProto.SentencePiece.Type
 	(*TrainerSpec)(nil),                // 2: sentencepiece.TrainerSpec
@@ -1392,7 +1392,7 @@ func file_sentencepiece_model_proto_init() {
 		return
 	}
 	if !protoimpl.UnsafeEnabled {
-		file_sentencepiece_model_proto_msgTypes[0].Exporter = func(v interface{}, i int) interface{} {
+		file_sentencepiece_model_proto_msgTypes[0].Exporter = func(v any, i int) any {
 			switch v := v.(*TrainerSpec); i {
 			case 0:
 				return &v.state
@@ -1406,7 +1406,7 @@ func file_sentencepiece_model_proto_init() {
 				return nil
 			}
 		}
-		file_sentencepiece_model_proto_msgTypes[1].Exporter = func(v interface{}, i int) interface{} {
+		file_sentencepiece_model_proto_msgTypes[1].Exporter = func(v any, i int) any {
 			switch v := v.(*NormalizerSpec); i {
 			case 0:
 				return &v.state
@@ -1420,7 +1420,7 @@ func file_sentencepiece_model_proto_init() {
 				return nil
 			}
 		}
-		file_sentencepiece_model_proto_msgTypes[2].Exporter = func(v interface{}, i int) interface{} {
+		file_sentencepiece_model_proto_msgTypes[2].Exporter = func(v any, i int) any {
 			switch v := v.(*SelfTestData); i {
 			case 0:
 				return &v.state
@@ -1434,7 +1434,7 @@ func file_sentencepiece_model_proto_init() {
 				return nil
 			}
 		}
-		file_sentencepiece_model_proto_msgTypes[3].Exporter = func(v interface{}, i int) interface{} {
+		file_sentencepiece_model_proto_msgTypes[3].Exporter = func(v any, i int) any {
 			switch v := v.(*ModelProto); i {
 			case 0:
 				return &v.state
@@ -1448,7 +1448,7 @@ func file_sentencepiece_model_proto_init() {
 				return nil
 			}
 		}
-		file_sentencepiece_model_proto_msgTypes[4].Exporter = func(v interface{}, i int) interface{} {
+		file_sentencepiece_model_proto_msgTypes[4].Exporter = func(v any, i int) any {
 			switch v := v.(*SelfTestData_Sample); i {
 			case 0:
 				return &v.state
@@ -1460,7 +1460,7 @@ func file_sentencepiece_model_proto_init() {
 				return nil
 			}
 		}
-		file_sentencepiece_model_proto_msgTypes[5].Exporter = func(v interface{}, i int) interface{} {
+		file_sentencepiece_model_proto_msgTypes[5].Exporter = func(v any, i int) any {
 			switch v := v.(*ModelProto_SentencePiece); i {
 			case 0:
 				return &v.state

discover/cpu_common.go

@@ -12,7 +12,7 @@ func IsNUMA() bool {
 		// numa support in llama.cpp is linux only
 		return false
 	}
-	ids := map[string]interface{}{}
+	ids := map[string]any{}
 	packageIds, _ := filepath.Glob("/sys/devices/system/cpu/cpu*/topology/physical_package_id")
 	for _, packageId := range packageIds {
 		id, err := os.ReadFile(packageId)

discover/gpu_linux.go

@@ -111,6 +111,7 @@ func GetCPUDetails() ([]CPU, error) {
 	if err != nil {
 		return nil, err
 	}
+	defer file.Close()
 	return linuxCPUDetails(file)
 }
 
@@ -168,13 +169,11 @@ func linuxCPUDetails(file io.Reader) ([]CPU, error) {
 	for id, s := range socketByID {
 		s.CoreCount = len(coreBySocket[id])
 		s.ThreadCount = 0
-		for _, tc := range threadsByCoreBySocket[id] {
-			s.ThreadCount += tc
-		}
 
 		// This only works if HT is enabled, consider a more reliable model, maybe cache size comparisons?
 		efficiencyCoreCount := 0
 		for _, threads := range threadsByCoreBySocket[id] {
+			s.ThreadCount += threads
 			if threads == 1 {
 				efficiencyCoreCount++
 			}

docs/api.md

@@ -558,6 +558,10 @@ Final response:
 {
   "model": "llama3.2",
   "created_at": "2023-08-04T19:22:45.499127Z",
+  "message": {
+    "role": "assistant",
+    "content": ""
+  },
   "done": true,
   "total_duration": 4883583458,
   "load_duration": 1334875,
@@ -1213,7 +1217,7 @@ Show information about a model including details, modelfile, template, parameter
 
 ```shell
 curl http://localhost:11434/api/show -d '{
-  "model": "llama3.2"
+  "model": "llava"
 }'
 ```
 
@@ -1256,7 +1260,11 @@ curl http://localhost:11434/api/show -d '{
     "tokenizer.ggml.pre": "llama-bpe",
     "tokenizer.ggml.token_type": [],        // populates if `verbose=true`
     "tokenizer.ggml.tokens": []             // populates if `verbose=true`
-  }
+  },
+  "capabilities": [
+    "completion",
+    "vision"
+  ],
 }
 ```
 

docs/benchmark.md

@@ -0,0 +1,59 @@
+# Benchmark
+
+Go benchmark tests that measure end-to-end performance of a running Ollama server. Run these tests to evaluate model inference performance on your hardware and measure the impact of code changes.
+
+## When to use
+
+Run these benchmarks when:
+- Making changes to the model inference engine
+- Modifying model loading/unloading logic
+- Changing prompt processing or token generation code
+- Implementing a new model architecture
+- Testing performance across different hardware setups
+
+## Prerequisites
+- Ollama server running locally with `ollama serve` on `127.0.0.1:11434`
+## Usage and Examples
+
+>[!NOTE]
+>All commands must be run from the root directory of the Ollama project.
+
+Basic syntax:
+```bash
+go test -bench=. ./benchmark/... -m $MODEL_NAME
+```
+
+Required flags:
+- `-bench=.`: Run all benchmarks
+- `-m`: Model name to benchmark
+
+Optional flags:
+- `-count N`: Number of times to run the benchmark (useful for statistical analysis)
+- `-timeout T`: Maximum time for the benchmark to run (e.g. "10m" for 10 minutes)
+
+Common usage patterns:
+
+Single benchmark run with a model specified:
+```bash
+go test -bench=. ./benchmark/... -m llama3.3
+```
+
+## Output metrics
+
+The benchmark reports several key metrics:
+
+- `gen_tok/s`: Generated tokens per second
+- `prompt_tok/s`: Prompt processing tokens per second
+- `ttft_ms`: Time to first token in milliseconds
+- `load_ms`: Model load time in milliseconds
+- `gen_tokens`: Total tokens generated
+- `prompt_tokens`: Total prompt tokens processed
+
+Each benchmark runs two scenarios:
+- Cold start: Model is loaded from disk for each test
+- Warm start: Model is pre-loaded in memory
+
+Three prompt lengths are tested for each scenario:
+- Short prompt (100 tokens)
+- Medium prompt (500 tokens)
+- Long prompt (1000 tokens)

docs/faq.md

@@ -20,7 +20,13 @@ Please refer to the [GPU docs](./gpu.md).
 
 ## How can I specify the context window size?
 
-By default, Ollama uses a context window size of 2048 tokens. This can be overridden with the `OLLAMA_CONTEXT_LENGTH` environment variable. For example, to set the default context length to 8K, use: `OLLAMA_CONTEXT_LENGTH=8192 ollama serve`.
+By default, Ollama uses a context window size of 2048 tokens. 
+
+This can be overridden with the `OLLAMA_CONTEXT_LENGTH` environment variable. For example, to set the default context window to 8K, use: 
+
+```shell
+OLLAMA_CONTEXT_LENGTH=8192 ollama serve
+```
 
 To change this when using `ollama run`, use `/set parameter`:
 

docs/troubleshooting.md

@@ -9,7 +9,7 @@ cat ~/.ollama/logs/server.log
 On **Linux** systems with systemd, the logs can be found with this command:
 
 ```shell
-journalctl -u ollama --no-pager
+journalctl -u ollama --no-pager --follow --pager-end 
 ```
 
 When you run Ollama in a **container**, the logs go to stdout/stderr in the container:

format/time_test.go

@@ -5,7 +5,7 @@ import (
 	"time"
 )
 
-func assertEqual(t *testing.T, a interface{}, b interface{}) {
+func assertEqual(t *testing.T, a any, b any) {
 	if a != b {
 		t.Errorf("Assert failed, expected %v, got %v", b, a)
 	}

fs/ggml/ggml.go

@@ -413,7 +413,7 @@ func Decode(rs io.ReadSeeker, maxArraySize int) (*GGML, int64, error) {
 	}, offset, nil
 }
 
-func (f GGML) GraphSize(context, batch uint64, kvCacheType string) (kv, partialOffload, fullOffload uint64) {
+func (f GGML) GraphSize(context, batch uint64, numParallel int, kvCacheType string) (kv []uint64, partialOffload, fullOffload uint64) {
 	embedding := f.KV().EmbeddingLength()
 	heads := f.KV().HeadCount()
 	headsKV := f.KV().HeadCountKV()
@@ -426,7 +426,10 @@ func (f GGML) GraphSize(context, batch uint64, kvCacheType string) (kv, partialO
 	layers := f.Tensors().GroupLayers()
 
 	bytesPerElement := kvCacheBytesPerElement(kvCacheType)
-	kv = uint64(float64(context*f.KV().BlockCount()*(embeddingHeadsK+embeddingHeadsV)*headsKV) * bytesPerElement)
+	kv = make([]uint64, f.KV().BlockCount())
+	for i := range kv {
+		kv[i] = uint64(float64(context*(embeddingHeadsK+embeddingHeadsV)*headsKV) * bytesPerElement)
+	}
 
 	switch f.KV().Architecture() {
 	case "llama":
@@ -460,16 +463,14 @@ func (f GGML) GraphSize(context, batch uint64, kvCacheType string) (kv, partialO
 	case "mllama":
 		var visionTokens, tiles uint64 = 1601, 4
 
-		if crossAttentionLayers, ok := f.KV()["mllama.attention.cross_attention_layers"].(*array); ok {
-			kv = headsKV *
-				(embeddingHeadsK + embeddingHeadsV) * // one for K, one for V
-				(2* // sizeof(float16)
-					(f.KV().BlockCount()-uint64(crossAttentionLayers.size))* // num non-cross attention layers
-					context +
-					4* // sizeof(float32)
-						uint64(crossAttentionLayers.size)* // num cross attention layers
-						visionTokens*
-						tiles)
+		crossAttentionLayers := f.KV().Uints("attention.cross_attention_layers")
+		for i := range kv {
+			if slices.Contains(crossAttentionLayers, uint32(i)) {
+				kv[i] = headsKV * (embeddingHeadsK + embeddingHeadsV) *
+					4 * // sizeof(float32)
+					visionTokens *
+					tiles
+			}
 		}
 
 		fullOffload = max(
@@ -505,6 +506,20 @@ func (f GGML) GraphSize(context, batch uint64, kvCacheType string) (kv, partialO
 				4*embeddingHeadsK*context*8+
 				embedding*embeddingHeadsK*heads*9/16,
 		)
+
+		// Gemma2 also has sliding window attention but we only have an optimized implementation in the Ollama
+		// engine. Gemma3 always uses the Ollama engine.
+		if f.KV().Architecture() == "gemma3" {
+			const gemma3GlobalCacheCount = 6
+			slidingWindow := (uint64(numParallel) * uint64(f.KV().Uint("attention.sliding_window"))) + batch
+			for i := range kv {
+				// Every 6th layer is a global layer, which is the full context size that has already been set. The other
+				// layers are the smaller local (sliding) layers.
+				if (i+1)%gemma3GlobalCacheCount != 0 {
+					kv[i] = uint64(float64(slidingWindow*(embeddingHeadsK+embeddingHeadsV)*headsKV) * bytesPerElement)
+				}
+			}
+		}
 	case "command-r":
 		fullOffload = max(
 			4*batch*(embedding+vocab),

integration/basic_test.go

@@ -22,7 +22,7 @@ func TestOrcaMiniBlueSky(t *testing.T) {
 		Model:  "orca-mini",
 		Prompt: "why is the sky blue?",
 		Stream: &stream,
-		Options: map[string]interface{}{
+		Options: map[string]any{
 			"temperature": 0,
 			"seed":        123,
 		},
@@ -39,7 +39,7 @@ func TestUnicode(t *testing.T) {
 		Model:  "deepseek-coder-v2:16b-lite-instruct-q2_K",
 		Prompt: "天空为什么是蓝色的?",
 		Stream: &stream,
-		Options: map[string]interface{}{
+		Options: map[string]any{
 			"temperature": 0,
 			"seed":        123,
 			// Workaround deepseek context shifting bug
@@ -61,7 +61,7 @@ func TestExtendedUnicodeOutput(t *testing.T) {
 		Model:  "gemma2:2b",
 		Prompt: "Output some smily face emoji",
 		Stream: &stream,
-		Options: map[string]interface{}{
+		Options: map[string]any{
 			"temperature": 0,
 			"seed":        123,
 		},
@@ -96,7 +96,7 @@ func TestUnicodeModelDir(t *testing.T) {
 		Model:  "orca-mini",
 		Prompt: "why is the sky blue?",
 		Stream: &stream,
-		Options: map[string]interface{}{
+		Options: map[string]any{
 			"temperature": 0,
 			"seed":        123,
 		},

integration/concurrency_test.go

@@ -25,7 +25,7 @@ func TestMultiModelConcurrency(t *testing.T) {
 				Prompt:    "why is the ocean blue?",
 				Stream:    &stream,
 				KeepAlive: &api.Duration{Duration: 10 * time.Second},
-				Options: map[string]interface{}{
+				Options: map[string]any{
 					"seed":        42,
 					"temperature": 0.0,
 				},
@@ -34,7 +34,7 @@ func TestMultiModelConcurrency(t *testing.T) {
 				Prompt:    "what is the origin of the us thanksgiving holiday?",
 				Stream:    &stream,
 				KeepAlive: &api.Duration{Duration: 10 * time.Second},
-				Options: map[string]interface{}{
+				Options: map[string]any{
 					"seed":        42,
 					"temperature": 0.0,
 				},

integration/context_test.go

@@ -23,7 +23,7 @@ func TestLongInputContext(t *testing.T) {
 		Model:  "llama2",
 		Prompt: "Oh, don’t speak to me of Austria. Perhaps I don’t understand things, but Austria never has wished, and does not wish, for war. She is betraying us! Russia alone must save Europe. Our gracious sovereign recognizes his high vocation and will be true to it. That is the one thing I have faith in! Our good and wonderful sovereign has to perform the noblest role on earth, and he is so virtuous and noble that God will not forsake him. He will fulfill his vocation and crush the hydra of revolution, which has become more terrible than ever in the person of this murderer and villain! We alone must avenge the blood of the just one.... Whom, I ask you, can we rely on?... England with her commercial spirit will not and cannot understand the Emperor Alexander’s loftiness of soul. She has refused to evacuate Malta. She wanted to find, and still seeks, some secret motive in our actions. What answer did Novosíltsev get? None. The English have not understood and cannot understand the self-abnegation of our Emperor who wants nothing for himself, but only desires the good of mankind. And what have they promised? Nothing! And what little they have promised they will not perform! Prussia has always declared that Buonaparte is invincible, and that all Europe is powerless before him.... And I don’t believe a word that Hardenburg says, or Haugwitz either. This famous Prussian neutrality is just a trap. I have faith only in God and the lofty destiny of our adored monarch. He will save Europe! What country is this referring to?",
 		Stream: &stream,
-		Options: map[string]interface{}{
+		Options: map[string]any{
 			"temperature": 0,
 			"seed":        123,
 			"num_ctx":     128,
@@ -50,7 +50,7 @@ func TestContextExhaustion(t *testing.T) {
 		Model:  "llama2",
 		Prompt: "Write me a story with a ton of emojis?",
 		Stream: &stream,
-		Options: map[string]interface{}{
+		Options: map[string]any{
 			"temperature": 0,
 			"seed":        123,
 			"num_ctx":     128,

integration/llm_image_test.go

@@ -19,7 +19,7 @@ func TestIntegrationLlava(t *testing.T) {
 		Model:  "llava:7b",
 		Prompt: "what does the text in this image say?",
 		Stream: &stream,
-		Options: map[string]interface{}{
+		Options: map[string]any{
 			"seed":        42,
 			"temperature": 0.0,
 		},
@@ -47,7 +47,7 @@ func TestIntegrationMllama(t *testing.T) {
 		Model:  "x/llama3.2-vision",
 		Prompt: "what does the text in this image say?",
 		Stream: &stream,
-		Options: map[string]interface{}{
+		Options: map[string]any{
 			"seed":        42,
 			"temperature": 0.0,
 		},
@@ -66,6 +66,35 @@ func TestIntegrationMllama(t *testing.T) {
 	DoGenerate(ctx, t, client, req, []string{resp}, 240*time.Second, 30*time.Second)
 }
 
+func TestIntegrationSplitBatch(t *testing.T) {
+	image, err := base64.StdEncoding.DecodeString(imageEncoding)
+	require.NoError(t, err)
+	req := api.GenerateRequest{
+		Model: "gemma3:4b",
+		// Fill up a chunk of the batch so the image will partially spill over into the next one
+		System: "Lorem ipsum dolor sit amet, consectetur adipiscing elit. Sed aliquet, justo in malesuada lobortis, odio ligula volutpat quam, quis faucibus ipsum magna quis sapien. Aliquam in venenatis diam, eu viverra magna. Phasellus imperdiet hendrerit volutpat. Vivamus sem ex, facilisis placerat felis non, dictum elementum est. Phasellus aliquam imperdiet lacus, eget placerat ligula sodales vel. Pellentesque nec auctor mi. Curabitur arcu nisi, faucibus eget nunc id, viverra interdum mi. Curabitur ornare ipsum ex, ac euismod ex aliquam in. Vestibulum id magna at purus accumsan fermentum. Proin scelerisque posuere nunc quis interdum. Maecenas sed mollis nisl. Etiam vitae ipsum interdum, placerat est quis, tincidunt velit. Nullam tempor nibh non lorem volutpat efficitur. Cras laoreet diam imperdiet ipsum auctor bibendum. Suspendisse ultrices urna sed metus sagittis suscipit. Quisque ullamcorper aliquam nibh ut mollis. Aenean dapibus mauris pharetra, venenatis elit ac, hendrerit odio. Cras vestibulum erat tempor, lobortis justo eu, lobortis ipsum. Nam laoreet dapibus sem. Proin vel diam ultrices, elementum ante et, ornare lectus. Proin eu accumsan nisl. Praesent ac ex vitae ipsum vulputate tristique facilisis sit amet lacus. Nullam faucibus magna a pellentesque pretium. Nunc lacinia ullamcorper sollicitudin. Donec vitae accumsan turpis, sed porttitor est. Donec porttitor mi vitae augue faucibus, vel mollis diam tincidunt.",
+		Prompt: "what does the text in this image say?",
+		Stream: &stream,
+		Options: map[string]any{
+			"seed":        42,
+			"temperature": 0.0,
+		},
+		Images: []api.ImageData{
+			image,
+		},
+	}
+
+	// Note: sometimes it returns "the ollamas" sometimes "the ollams"
+	resp := "the ollam"
+	ctx, cancel := context.WithTimeout(context.Background(), 3*time.Minute)
+	defer cancel()
+	client, _, cleanup := InitServerConnection(ctx, t)
+	defer cleanup()
+	require.NoError(t, PullIfMissing(ctx, client, req.Model))
+	// llava models on CPU can be quite slow to start,
+	DoGenerate(ctx, t, client, req, []string{resp}, 120*time.Second, 30*time.Second)
+}
+
 const imageEncoding = `iVBORw0KGgoAAAANSUhEUgAAANIAAAB4CAYAAACHHqzKAAAAAXNSR0IArs4c6QAAAIRlWElmTU0AKgAAAAgABQESAAMAAAABAAEAAAEaAAUAAAABAAAASgEb
 AAUAAAABAAAAUgEoAAMAAAABAAIAAIdpAAQAAAABAAAAWgAAAAAAAABIAAAAAQAAAEgAAAABAAOgAQADAAAAAQABAACgAgAEAAAAAQAAANKgAwAEAAAAAQAA
 AHgAAAAAXdsepgAAAAlwSFlzAAALEwAACxMBAJqcGAAAAVlpVFh0WE1MOmNvbS5hZG9iZS54bXAAAAAAADx4OnhtcG1ldGEgeG1sbnM6eD0iYWRvYmU6bnM6

integration/llm_test.go

@@ -20,7 +20,7 @@ var (
 			Model:  "orca-mini",
 			Prompt: "why is the ocean blue?",
 			Stream: &stream,
-			Options: map[string]interface{}{
+			Options: map[string]any{
 				"seed":        42,
 				"temperature": 0.0,
 			},
@@ -28,7 +28,7 @@ var (
 			Model:  "orca-mini",
 			Prompt: "what is the origin of the us thanksgiving holiday?",
 			Stream: &stream,
-			Options: map[string]interface{}{
+			Options: map[string]any{
 				"seed":        42,
 				"temperature": 0.0,
 			},

integration/max_queue_test.go

@@ -32,7 +32,7 @@ func TestMaxQueue(t *testing.T) {
 	req := api.GenerateRequest{
 		Model:  "orca-mini",
 		Prompt: "write a long historical fiction story about christopher columbus.  use at least 10 facts from his actual journey",
-		Options: map[string]interface{}{
+		Options: map[string]any{
 			"seed":        42,
 			"temperature": 0.0,
 		},

integration/utils_test.go

@@ -291,7 +291,7 @@ func GenerateRequests() ([]api.GenerateRequest, [][]string) {
 				Prompt:    "why is the ocean blue?",
 				Stream:    &stream,
 				KeepAlive: &api.Duration{Duration: 10 * time.Second},
-				Options: map[string]interface{}{
+				Options: map[string]any{
 					"seed":        42,
 					"temperature": 0.0,
 				},
@@ -300,7 +300,7 @@ func GenerateRequests() ([]api.GenerateRequest, [][]string) {
 				Prompt:    "why is the color of dirt brown?",
 				Stream:    &stream,
 				KeepAlive: &api.Duration{Duration: 10 * time.Second},
-				Options: map[string]interface{}{
+				Options: map[string]any{
 					"seed":        42,
 					"temperature": 0.0,
 				},
@@ -309,7 +309,7 @@ func GenerateRequests() ([]api.GenerateRequest, [][]string) {
 				Prompt:    "what is the origin of the us thanksgiving holiday?",
 				Stream:    &stream,
 				KeepAlive: &api.Duration{Duration: 10 * time.Second},
-				Options: map[string]interface{}{
+				Options: map[string]any{
 					"seed":        42,
 					"temperature": 0.0,
 				},
@@ -318,7 +318,7 @@ func GenerateRequests() ([]api.GenerateRequest, [][]string) {
 				Prompt:    "what is the origin of independence day?",
 				Stream:    &stream,
 				KeepAlive: &api.Duration{Duration: 10 * time.Second},
-				Options: map[string]interface{}{
+				Options: map[string]any{
 					"seed":        42,
 					"temperature": 0.0,
 				},
@@ -327,7 +327,7 @@ func GenerateRequests() ([]api.GenerateRequest, [][]string) {
 				Prompt:    "what is the composition of air?",
 				Stream:    &stream,
 				KeepAlive: &api.Duration{Duration: 10 * time.Second},
-				Options: map[string]interface{}{
+				Options: map[string]any{
 					"seed":        42,
 					"temperature": 0.0,
 				},

kvcache/cache.go

@@ -43,8 +43,13 @@ type Cache interface {
 
 	// ** cache management **
 
-	// Init sets up runtime parameters
-	Init(backend ml.Backend, dtype ml.DType, capacity int32)
+	// Init sets up runtime parameters.
+	// backend: Used to allocate cache data storage and execute management operations (such as defrag)
+	// dtype: The data type for storing cache entries
+	// maxSequences: The maximum number of sequences stored in the cache - across all batches
+	// capacity: The number of cache entries to store, per sequence
+	// maxBatch: The maximum number of tokens that can occur in a single batch
+	Init(backend ml.Backend, dtype ml.DType, maxSequences, capacity, maxBatch int)
 
 	// Close closes the cache and frees resources associated with it
 	Close()
@@ -52,11 +57,16 @@ type Cache interface {
 	// StartForward is called before the start of the model's forward pass.
 	// For each token in the coming batch, there must be a corresponding
 	// entry in positions and seqs.
-	StartForward(ctx ml.Context, opts input.Options) error
+	StartForward(ctx ml.Context, batch input.Batch) error
 
 	// CopyPrefix copies tokens in the range [0, len) from srcSeq to dstSeq
 	CopyPrefix(srcSeq, dstSeq int, len int32)
 
+	// CanResume returns true if the cache can continue with the next token at
+	// the given position and sequence. Assumes that the caller has already
+	// verified the contents of the cache.
+	CanResume(seq int, pos int32) bool
+
 	// Remove deletes tokens in the range [beginIndex, endIndex) from seq. Set
 	// endIndex to math.MaxInt32 to remove everything starting at beginIndex.
 	//

kvcache/causal.go

@@ -20,7 +20,6 @@ type shiftFn func(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, e
 // The mask is of shape history size, batch size
 type Causal struct {
 	DType      ml.DType
-	Capacity   int32
 	windowSize int32
 
 	opts CausalOptions
@@ -98,7 +97,7 @@ func NewSWACache(windowSize int32, shift shiftFn) *Causal {
 	}
 }
 
-func (c *Causal) Init(backend ml.Backend, dtype ml.DType, capacity int32) {
+func (c *Causal) Init(backend ml.Backend, dtype ml.DType, maxSequences, capacity, maxBatch int) {
 	if c.config == nil {
 		var config ml.CacheConfig
 		if cc, ok := backend.(ml.BackendCacheConfig); ok {
@@ -119,9 +118,16 @@ func (c *Causal) Init(backend ml.Backend, dtype ml.DType, capacity int32) {
 		c.config.MaskDType = ml.DTypeF32
 	}
 
+	var cacheSize int
+	if c.windowSize == math.MaxInt32 || capacity < int(c.windowSize) {
+		cacheSize = maxSequences * capacity
+	} else {
+		cacheSize = (maxSequences * int(c.windowSize)) + maxBatch
+	}
+	cacheSize = roundUp(cacheSize, c.config.CachePadding)
+	c.cells = make([]cacheCell, cacheSize)
+
 	c.DType = dtype
-	c.Capacity = int32(roundUp(int(capacity), c.config.CachePadding))
-	c.cells = make([]cacheCell, c.Capacity)
 	c.cellRanges = make(map[int]cellRange)
 	c.backend = backend
 }
@@ -140,12 +146,14 @@ func (c *Causal) Close() {
 	}
 }
 
-func (c *Causal) StartForward(ctx ml.Context, opts input.Options) error {
-	c.curBatchSize = len(opts.Positions)
-	c.curSequences = opts.Sequences
-	c.curPositions = opts.Positions
+func (c *Causal) StartForward(ctx ml.Context, batch input.Batch) error {
+	c.curBatchSize = len(batch.Positions)
+	c.curSequences = batch.Sequences
+	c.curPositions = batch.Positions
 	c.opts.Except = nil
 
+	c.updateSlidingWindow()
+
 	var err error
 	c.curLoc, err = c.findStartLoc()
 	if errors.Is(err, ErrKvCacheFull) {
@@ -157,8 +165,8 @@ func (c *Causal) StartForward(ctx ml.Context, opts input.Options) error {
 	}
 
 	c.curCellRange = newRange()
-	for i, pos := range opts.Positions {
-		seq := opts.Sequences[i]
+	for i, pos := range batch.Positions {
+		seq := batch.Sequences[i]
 
 		c.cells[c.curLoc+i] = cacheCell{pos: pos, sequences: []int{seq}}
 
@@ -210,7 +218,51 @@ func (c *Causal) findStartLoc() (int, error) {
 		}
 	}
 
-	return 0, fmt.Errorf("%w (length: %v)", ErrKvCacheFull, c.Capacity)
+	return 0, fmt.Errorf("%w (length: %v)", ErrKvCacheFull, len(c.cells))
+}
+
+func (c *Causal) updateSlidingWindow() {
+	if c.windowSize == math.MaxInt32 {
+		return
+	}
+
+	// create a map of unique sequences to the lowest position in that sequence
+	lowestPos := make(map[int]int32)
+	for i := range c.curPositions {
+		seq := c.curSequences[i]
+
+		pos, ok := lowestPos[seq]
+		if !ok {
+			pos = c.curPositions[i]
+		} else if c.curPositions[i] < pos {
+			pos = c.curPositions[i]
+		}
+
+		lowestPos[seq] = pos
+	}
+
+	// delete any entries that are beyond the window of the oldest position in the sequence
+	for seq, pos := range lowestPos {
+		oldRange, ok := c.cellRanges[seq]
+		if !ok {
+			continue
+		}
+
+		newRange := newRange()
+
+		for i := oldRange.min; i <= oldRange.max; i++ {
+			if slices.Contains(c.cells[i].sequences, seq) {
+				if c.cells[i].pos < pos-c.windowSize {
+					c.cells[i].sequences = slices.DeleteFunc(c.cells[i].sequences, func(s int) bool { return s == seq })
+				} else {
+					newRange.min = min(newRange.min, i)
+					newRange.max = max(newRange.max, i)
+				}
+			}
+		}
+
+		c.cellRanges[seq] = newRange
+	}
 }
 
 func roundDown(length, pad int) int {
@@ -265,7 +317,7 @@ func (c *Causal) buildMask(ctx ml.Context) (ml.Tensor, error) {
 	return maskTensor, nil
 }
 
-func (c *Causal) moveCells(ctx ml.Context, src, dst, len int) {
+func (c *Causal) moveCells(ctx ml.Context, src, dst, length int) {
 	for i, key := range c.keys {
 		if key == nil {
 			continue
@@ -275,8 +327,8 @@ func (c *Causal) moveCells(ctx ml.Context, src, dst, len int) {
 		numKVHeads := key.Dim(1)
 		rowSize := key.Stride(2)
 
-		kSrcView := key.View(ctx, rowSize*src, kHeadDim*numKVHeads*len)
-		kDstView := key.View(ctx, rowSize*dst, kHeadDim*numKVHeads*len)
+		kSrcView := key.View(ctx, rowSize*src, kHeadDim*numKVHeads*length)
+		kDstView := key.View(ctx, rowSize*dst, kHeadDim*numKVHeads*length)
 
 		value := c.values[i]
 		var vSrcView, vDstView ml.Tensor
@@ -284,14 +336,14 @@ func (c *Causal) moveCells(ctx ml.Context, src, dst, len int) {
 			vHeadDim := value.Dim(1)
 			elemSize := value.Stride(0)
 
-			vSrcView = value.View(ctx, elemSize*src, len, int(c.Capacity)*elemSize, vHeadDim*numKVHeads)
-			vDstView = value.View(ctx, elemSize*dst, len, int(c.Capacity)*elemSize, vHeadDim*numKVHeads)
+			vSrcView = value.View(ctx, elemSize*src, length, len(c.cells)*elemSize, vHeadDim*numKVHeads)
+			vDstView = value.View(ctx, elemSize*dst, length, len(c.cells)*elemSize, vHeadDim*numKVHeads)
 		} else {
 			vHeadDim := value.Dim(0)
 			rowSize := value.Stride(2)
 
-			vSrcView = value.View(ctx, rowSize*src, vHeadDim*numKVHeads*len)
-			vDstView = value.View(ctx, rowSize*dst, vHeadDim*numKVHeads*len)
+			vSrcView = value.View(ctx, rowSize*src, vHeadDim*numKVHeads*length)
+			vDstView = value.View(ctx, rowSize*dst, vHeadDim*numKVHeads*length)
 		}
 
 		ctx.Forward(
@@ -321,7 +373,8 @@ func (c *Causal) defrag() {
 	ctx := c.backend.NewContext()
 
 	// For every move, 6 tensors are required per layer (2 views and a
-	// copy for each of k and v).
+	// copy for each of k and v). We also need to refer to the original
+	// k and v cache tensors - once per layer, not per move.
 	layers := 0
 	for _, key := range c.keys {
 		if key == nil {
@@ -330,7 +383,7 @@ func (c *Causal) defrag() {
 		layers++
 	}
 
-	maxMoves := ctx.MaxGraphNodes() / (6 * layers)
+	maxMoves := (ctx.MaxGraphNodes() - 2*layers) / (6 * layers)
 	moves := 0
 
 	var pendingSrc, pendingDst, pendingLen int
@@ -479,14 +532,14 @@ func (c *Causal) Put(ctx ml.Context, key, value ml.Tensor) {
 	}
 
 	if _, ok := c.keys[c.curLayer]; !ok {
-		c.keys[c.curLayer] = c.ctxs[c.curLayer].Zeros(c.DType, kHeadDim, numKVHeads, int(c.Capacity))
+		c.keys[c.curLayer] = c.ctxs[c.curLayer].Zeros(c.DType, kHeadDim, numKVHeads, len(c.cells))
 	}
 
 	if _, ok := c.values[c.curLayer]; !ok {
 		if c.config.PermutedV {
-			c.values[c.curLayer] = c.ctxs[c.curLayer].Zeros(c.DType, int(c.Capacity), vHeadDim, numKVHeads)
+			c.values[c.curLayer] = c.ctxs[c.curLayer].Zeros(c.DType, len(c.cells), vHeadDim, numKVHeads)
 		} else {
-			c.values[c.curLayer] = c.ctxs[c.curLayer].Zeros(c.DType, vHeadDim, numKVHeads, int(c.Capacity))
+			c.values[c.curLayer] = c.ctxs[c.curLayer].Zeros(c.DType, vHeadDim, numKVHeads, len(c.cells))
 		}
 	}
 
@@ -497,7 +550,7 @@ func (c *Causal) Put(ctx ml.Context, key, value ml.Tensor) {
 		elemSize := c.values[c.curLayer].Stride(0)
 
 		value = value.Permute(ctx, 1, 2, 0, 3)
-		ctx.Forward(value.Copy(ctx, c.values[c.curLayer].View(ctx, elemSize*c.curLoc, batchSize, int(c.Capacity)*elemSize, vHeadDim*numKVHeads)))
+		ctx.Forward(value.Copy(ctx, c.values[c.curLayer].View(ctx, elemSize*c.curLoc, batchSize, len(c.cells)*elemSize, vHeadDim*numKVHeads)))
 	} else {
 		rowSize := c.values[c.curLayer].Stride(2)
 
@@ -528,6 +581,35 @@ func (c *Causal) CopyPrefix(srcSeq, dstSeq int, len int32) {
 	c.cellRanges[dstSeq] = seqRange
 }
 
+func (c *Causal) CanResume(seq int, pos int32) bool {
+	if c.windowSize == math.MaxInt32 {
+		return true
+	}
+
+	seqRange, ok := c.cellRanges[seq]
+	if !ok {
+		return false
+	}
+
+	// for sliding window, check that the window of the new sequence is contained in
+	// the window of what we are storing
+	var last int32 = -1
+	for i := seqRange.min; i <= seqRange.max; i++ {
+		if slices.Contains(c.cells[i].sequences, seq) {
+			last = max(last, c.cells[i].pos)
+		}
+	}
+
+	if last == -1 {
+		return false
+	}
+
+	lastWindowStart := max(0, last-c.windowSize)
+	posWindowStart := max(0, pos-c.windowSize)
+
+	return posWindowStart >= lastWindowStart
+}
+
 func (c *Causal) shift(seq int, beginIndex, offset int32) error {
 	if c.shiftFn == nil {
 		return ErrNotSupported
@@ -582,6 +664,12 @@ func (c *Causal) shift(seq int, beginIndex, offset int32) error {
 }
 
 func (c *Causal) Remove(seq int, beginIndex, endIndex int32) error {
+	// TODO(jessegross): We should check to see if removing the middle of the sequence will
+	// cause the sliding window to encompass tokens that we no longer have. If so, then we
+	// should return an error, which will trigger the runner to evaluate the full history and
+	// rebuild the window. However, if we have multimodal inputs in our history, this reuse
+	// results in use after free, so we don't do it for now.
+
 	var offset int32
 	if endIndex != math.MaxInt32 {
 		offset = beginIndex - endIndex
@@ -596,8 +684,7 @@ func (c *Causal) Remove(seq int, beginIndex, endIndex int32) error {
 			} else {
 				if c.cells[i].pos >= endIndex {
 					if slices.ContainsFunc(c.cells[i].sequences, func(s int) bool { return s != seq }) {
-						// TODO(jessegross): Need to be careful about data shared between sequences
-						return errors.New("shifting on cells shared by multiple sequences not yet implemented")
+						return errors.New("shifting cells shared by multiple sequences not supported")
 					}
 
 					c.cells[i].pos += offset

kvcache/causal_test.go

@@ -25,7 +25,7 @@ func TestStore(t *testing.T) {
 	cache := NewCausalCache(nil)
 	defer cache.Close()
 
-	cache.Init(backend, ml.DTypeF16, 16)
+	cache.Init(backend, ml.DTypeF16, 1, 16, 16)
 
 	tests := []testCase{
 		{
@@ -58,11 +58,11 @@ func TestSWA(t *testing.T) {
 	cache := NewSWACache(1, nil)
 	defer cache.Close()
 
-	cache.Init(backend, ml.DTypeF32, 16)
+	cache.Init(backend, ml.DTypeF16, 1, 16, 16)
 
 	tests := []testCase{
 		{
-			name:          "SlidingWindow",
+			name:          "FirstBatch",
 			in:            []float32{1, 2, 3, 4},
 			inShape:       []int{1, 1, 4},
 			seqs:          []int{0, 0, 0, 0},
@@ -71,6 +71,16 @@ func TestSWA(t *testing.T) {
 			expectedShape: []int{1, 1, 4},
 			expectedMask:  []float32{0, float32(math.Inf(-1)), float32(math.Inf(-1)), float32(math.Inf(-1)), 0, 0, float32(math.Inf(-1)), float32(math.Inf(-1)), float32(math.Inf(-1)), 0, 0, float32(math.Inf(-1)), float32(math.Inf(-1)), float32(math.Inf(-1)), 0, 0},
 		},
+		{
+			name:          "SecondBatch",
+			in:            []float32{5, 6},
+			inShape:       []int{1, 1, 2},
+			seqs:          []int{0, 0},
+			pos:           []int32{4, 5},
+			expected:      []float32{5, 6, 3, 4},
+			expectedShape: []int{1, 1, 4},
+			expectedMask:  []float32{0, float32(math.Inf(-1)), float32(math.Inf(-1)), 0, 0, 0, float32(math.Inf(-1)), float32(math.Inf(-1))},
+		},
 	}
 
 	testCache(t, backend, cache, tests)
@@ -81,7 +91,7 @@ func TestSequences(t *testing.T) {
 	cache := NewCausalCache(nil)
 	defer cache.Close()
 
-	cache.Init(backend, ml.DTypeF16, 16)
+	cache.Init(backend, ml.DTypeF16, 1, 16, 16)
 
 	tests := []testCase{
 		{
@@ -116,7 +126,7 @@ func TestRemove(t *testing.T) {
 	})
 	defer cache.Close()
 
-	cache.Init(backend, ml.DTypeF16, 16)
+	cache.Init(backend, ml.DTypeF16, 1, 16, 16)
 
 	tests := []testCase{
 		{
@@ -181,7 +191,7 @@ func TestDefrag(t *testing.T) {
 	})
 	defer cache.Close()
 
-	cache.Init(backend, ml.DTypeF16, 16)
+	cache.Init(backend, ml.DTypeF16, 1, 16, 16)
 
 	tests := []testCase{
 		{
@@ -229,7 +239,7 @@ func TestCopy(t *testing.T) {
 	cache := NewCausalCache(func(ctx ml.Context, layer int, key, shift ml.Tensor) (ml.Tensor, error) { return key, nil })
 	defer cache.Close()
 
-	cache.Init(backend, ml.DTypeF16, 16)
+	cache.Init(backend, ml.DTypeF16, 1, 16, 16)
 
 	tests := []testCase{
 		{
@@ -270,7 +280,7 @@ func testCache(t *testing.T, backend ml.Backend, cache Cache, tests []testCase)
 			context := backend.NewContext()
 			defer context.Close()
 
-			err := cache.StartForward(context, input.Options{Positions: test.pos, Sequences: test.seqs})
+			err := cache.StartForward(context, input.Batch{Positions: test.pos, Sequences: test.seqs})
 			if err != nil {
 				panic(err)
 			}
@@ -290,6 +300,77 @@ func testCache(t *testing.T, backend ml.Backend, cache Cache, tests []testCase)
 	}
 }
 
+func TestCanResume(t *testing.T) {
+	backend := &testBackend{}
+	windowSize := int32(4)
+	cache := NewSWACache(windowSize, nil)
+	defer cache.Close()
+
+	cache.Init(backend, ml.DTypeF16, 1, 16, 16)
+
+	context := backend.NewContext()
+	defer context.Close()
+
+	err := cache.StartForward(context, input.Batch{
+		Positions: []int32{0, 1, 2, 3},
+		Sequences: []int{0, 0, 0, 0},
+	})
+	if err != nil {
+		t.Fatalf("StartForward failed: %v", err)
+	}
+
+	cache.SetLayer(0)
+	tensor, _ := context.FromFloatSlice([]float32{1, 2, 3, 4}, 1, 1, 4)
+	cache.Put(context, tensor, tensor)
+
+	// with window size 4, nothing has slid out of the window yet
+	if !cache.CanResume(0, 0) {
+		t.Errorf("CanResume(0, 0) = false, want true (within window)")
+	}
+	if !cache.CanResume(0, 1) {
+		t.Errorf("CanResume(0, 1) = false, want true (within window)")
+	}
+	if !cache.CanResume(0, 2) {
+		t.Errorf("CanResume(0, 2) = false, want true (within window)")
+	}
+	if !cache.CanResume(0, 3) {
+		t.Errorf("CanResume(0, 3) = false, want true (latest position)")
+	}
+
+	// shift window by adding position 4
+	err = cache.StartForward(context, input.Batch{
+		Positions: []int32{4, 5},
+		Sequences: []int{0, 0},
+	})
+	if err != nil {
+		t.Fatalf("StartForward failed: %v", err)
+	}
+
+	cache.SetLayer(0)
+	tensor, _ = context.FromFloatSlice([]float32{5, 6}, 1, 1, 2)
+	cache.Put(context, tensor, tensor)
+
+	// only the latest position has overlapping windows
+	if cache.CanResume(0, 0) {
+		t.Errorf("after shift: CanResume(0, 0) = true, want false (outside window)")
+	}
+	if cache.CanResume(0, 1) {
+		t.Errorf("after shift: CanResume(0, 1) = true, want false (outside window)")
+	}
+	if cache.CanResume(0, 2) {
+		t.Errorf("after shift: CanResume(0, 2) = true, want false (outside window)")
+	}
+	if cache.CanResume(0, 3) {
+		t.Errorf("after shift: CanResume(0, 3) = true, want false (outside window)")
+	}
+	if cache.CanResume(0, 4) {
+		t.Errorf("after shift: CanResume(0, 4) = true, want false (outside window)")
+	}
+	if !cache.CanResume(0, 5) {
+		t.Errorf("after shift: CanResume(0, 5) = false, want true (latest position)")
+	}
+}
+
 type testBackend struct{}
 
 func (b *testBackend) Config() ml.Config {
@@ -352,7 +433,6 @@ func (c *testContext) FromIntSlice(s []int32, shape ...int) (ml.Tensor, error) {
 }
 
 func (c *testContext) Input() ml.Context    { return c }
-func (c *testContext) Output() ml.Context   { return c }
 func (c *testContext) Layer(int) ml.Context { return c }
 
 func (c *testContext) Forward(...ml.Tensor) ml.Context { return c }

kvcache/encoder.go

@@ -49,7 +49,7 @@ func NewEncoderCache() *EncoderCache {
 	}
 }
 
-func (c *EncoderCache) Init(backend ml.Backend, dtype ml.DType, capacity int32) {
+func (c *EncoderCache) Init(backend ml.Backend, dtype ml.DType, maxSequences, capacity, maxBatch int) {
 	if c.config == nil {
 		var config ml.CacheConfig
 		if cc, ok := backend.(ml.BackendCacheConfig); ok {
@@ -58,6 +58,10 @@ func (c *EncoderCache) Init(backend ml.Backend, dtype ml.DType, capacity int32)
 		c.config = &config
 	}
 
+	if maxSequences > 1 {
+		panic(fmt.Errorf("encoder cache does not support multiple sequences; requested: %v", maxSequences))
+	}
+
 	if c.config.CachePadding != 0 && c.config.CachePadding != 1 {
 		panic(fmt.Errorf("encoder cache is unable to enforce requested CachePadding (%v)", c.config.CachePadding))
 	}
@@ -79,10 +83,10 @@ func (c *EncoderCache) Close() {
 	}
 }
 
-func (c *EncoderCache) StartForward(ctx ml.Context, opts input.Options) error {
+func (c *EncoderCache) StartForward(ctx ml.Context, batch input.Batch) error {
 	// We work with the most recent image
-	if len(opts.Multimodal) > 0 {
-		c.curPos = opts.Positions[opts.Multimodal[len(opts.Multimodal)-1].Index]
+	if len(batch.Multimodal) > 0 {
+		c.curPos = batch.Positions[batch.Multimodal[len(batch.Multimodal)-1].Index]
 	}
 
 	return nil
@@ -130,6 +134,10 @@ func (c *EncoderCache) CopyPrefix(srcSeq, dstSeq int, len int32) {
 	panic("encoder cache does not support multiple sequences")
 }
 
+func (c *EncoderCache) CanResume(seq int, pos int32) bool {
+	return true
+}
+
 func (c *EncoderCache) Remove(seq int, beginIndex, endIndex int32) error {
 	if c.encoderPos >= beginIndex && c.encoderPos < endIndex {
 		c.encoderCached = false

kvcache/wrapper.go

@@ -23,9 +23,9 @@ func NewWrapperCache(caches ...Cache) *WrapperCache {
 	}
 }
 
-func (c *WrapperCache) Init(backend ml.Backend, dtype ml.DType, capacity int32) {
+func (c *WrapperCache) Init(backend ml.Backend, dtype ml.DType, maxSequences, capacity, maxBatch int) {
 	for _, cache := range c.caches {
-		cache.Init(backend, dtype, capacity)
+		cache.Init(backend, dtype, maxSequences, capacity, maxBatch)
 	}
 }
 
@@ -41,14 +41,14 @@ func (c *WrapperCache) Close() {
 	}
 }
 
-func (c *WrapperCache) StartForward(ctx ml.Context, opts input.Options) error {
+func (c *WrapperCache) StartForward(ctx ml.Context, batch input.Batch) error {
 	for i, cache := range c.caches {
-		err := cache.StartForward(ctx, opts)
+		err := cache.StartForward(ctx, batch)
 		if err != nil {
 			// unwind on error - Remove with endIndex set to math.MaxInt32 does not fail
 			for j := i - 1; j >= 0; j-- {
-				for k := range opts.Positions {
-					_ = c.caches[j].Remove(opts.Sequences[k], opts.Positions[k], math.MaxInt32)
+				for k := range batch.Positions {
+					_ = c.caches[j].Remove(batch.Sequences[k], batch.Positions[k], math.MaxInt32)
 				}
 			}
 			return err
@@ -87,6 +87,16 @@ func (c *WrapperCache) CopyPrefix(srcSeq, dstSeq int, len int32) {
 	}
 }
 
+func (c *WrapperCache) CanResume(seq int, pos int32) bool {
+	for _, cache := range c.caches {
+		if !cache.CanResume(seq, pos) {
+			return false
+		}
+	}
+
+	return true
+}
+
 func (c *WrapperCache) Remove(seq int, beginIndex, endIndex int32) error {
 	// If the one of these fails, the caller is supposed to retry with endIndex set to math.MaxInt32, which should not fail
 	for _, cache := range c.caches {

llama/llama.cpp/src/llama-arch.cpp

@@ -37,6 +37,7 @@ static const std::map<llm_arch, const char *> LLM_ARCH_NAMES = {
     { LLM_ARCH_MINICPM3,         "minicpm3"         },
     { LLM_ARCH_GEMMA,            "gemma"            },
     { LLM_ARCH_GEMMA2,           "gemma2"           },
+    { LLM_ARCH_GEMMA3,           "gemma3"           },
     { LLM_ARCH_STARCODER2,       "starcoder2"       },
     { LLM_ARCH_MAMBA,            "mamba"            },
     { LLM_ARCH_XVERSE,           "xverse"           },
@@ -804,6 +805,24 @@ static const std::map<llm_arch, std::map<llm_tensor, const char *>> LLM_TENSOR_N
             { LLM_TENSOR_FFN_POST_NORM,   "blk.%d.post_ffw_norm" },
         },
     },
+    {
+        LLM_ARCH_GEMMA3,
+        {
+            { LLM_TENSOR_TOKEN_EMBD,      "token_embd" },
+            { LLM_TENSOR_OUTPUT_NORM,     "output_norm" },
+            { LLM_TENSOR_ATTN_NORM,       "blk.%d.attn_norm" },
+            { LLM_TENSOR_ATTN_Q,          "blk.%d.attn_q" },
+            { LLM_TENSOR_ATTN_K,          "blk.%d.attn_k" },
+            { LLM_TENSOR_ATTN_V,          "blk.%d.attn_v" },
+            { LLM_TENSOR_ATTN_OUT,        "blk.%d.attn_output" },
+            { LLM_TENSOR_ATTN_POST_NORM,  "blk.%d.post_attention_norm" },
+            { LLM_TENSOR_FFN_NORM,        "blk.%d.ffn_norm" },
+            { LLM_TENSOR_FFN_GATE,        "blk.%d.ffn_gate" },
+            { LLM_TENSOR_FFN_DOWN,        "blk.%d.ffn_down" },
+            { LLM_TENSOR_FFN_UP,          "blk.%d.ffn_up" },
+            { LLM_TENSOR_FFN_POST_NORM,   "blk.%d.post_ffw_norm" },
+        },
+    },
     {
         LLM_ARCH_STARCODER2,
         {

llama/llama.cpp/src/llama-arch.h

@@ -41,6 +41,7 @@ enum llm_arch {
     LLM_ARCH_MINICPM3,
     LLM_ARCH_GEMMA,
     LLM_ARCH_GEMMA2,
+    LLM_ARCH_GEMMA3,
     LLM_ARCH_STARCODER2,
     LLM_ARCH_MAMBA,
     LLM_ARCH_XVERSE,

llama/llama.cpp/src/llama-model.cpp

@@ -878,6 +878,9 @@ void llama_model::load_hparams(llama_model_loader & ml) {
                     default: type = LLM_TYPE_UNKNOWN;
                }
             } break;
+        case LLM_ARCH_GEMMA3:
+            {
+            } break;
         case LLM_ARCH_STARCODER2:
             {
                 ml.get_key(LLM_KV_ATTENTION_LAYERNORM_EPS, hparams.f_norm_eps);
@@ -2537,6 +2540,9 @@ bool llama_model::load_tensors(llama_model_loader & ml) {
                         layer.ffn_post_norm = create_tensor(tn(LLM_TENSOR_FFN_POST_NORM, "weight", i), {n_embd}, 0);
                     }
                 } break;
+            case LLM_ARCH_GEMMA3:
+                {
+                } break;
             case LLM_ARCH_STARCODER2:
                 {
                     tok_embd = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, 0);
@@ -4029,6 +4035,7 @@ enum llama_rope_type llama_model_rope_type(const struct llama_model * model) {
         case LLM_ARCH_PHIMOE:
         case LLM_ARCH_GEMMA:
         case LLM_ARCH_GEMMA2:
+        case LLM_ARCH_GEMMA3:
         case LLM_ARCH_STARCODER2:
         case LLM_ARCH_OPENELM:
         case LLM_ARCH_GPTNEOX:

llama/llama.cpp/src/llama-quant.cpp

@@ -737,6 +737,15 @@ static void llama_model_quantize_impl(const std::string & fname_inp, const std::
         // This used to be a regex, but <regex> has an extreme cost to compile times.
         bool quantize = name.rfind("weight") == name.size() - 6; // ends with 'weight'?
 
+        // don't quantize vision stuff
+        quantize &= name.find("v.blk.") == std::string::npos;
+
+        quantize &= name.find("mm.mm_input_projection.weight") == std::string::npos;
+        quantize &= name.find("mm.mm_soft_emb_norm.weight") == std::string::npos;
+        quantize &= name.find("v.patch_embedding.weight") == std::string::npos;
+        quantize &= name.find("v.position_embedding.weight") == std::string::npos;
+        quantize &= name.find("v.post_layernorm.weight") == std::string::npos;
+
         // quantize only 2D and 3D tensors (experts)
         quantize &= (ggml_n_dims(tensor) >= 2);
 

llama/llama.go

@@ -166,6 +166,10 @@ func (c *Context) KvCacheDefrag() {
 	C.llama_kv_cache_defrag(c.c)
 }
 
+func (c *Context) KvCacheCanShift() bool {
+	return bool(C.llama_kv_cache_can_shift(c.c))
+}
+
 // Get the embeddings for a sequence id
 func (c *Context) GetEmbeddingsSeq(seqId int) []float32 {
 	e := unsafe.Pointer(C.llama_get_embeddings_seq(c.c, C.int(seqId)))

llama/patches/0021-gemma3-quantization.patch

@@ -0,0 +1,113 @@
+From 0000000000000000000000000000000000000000 Mon Sep 17 00:00:00 2001
+From: Patrick Devine <patrick@infrahq.com>
+Date: Fri, 14 Mar 2025 16:33:23 -0700
+Subject: [PATCH] gemma3 quantization
+
+---
+ src/llama-arch.cpp  | 19 +++++++++++++++++++
+ src/llama-arch.h    |  1 +
+ src/llama-model.cpp |  7 +++++++
+ src/llama-quant.cpp |  9 +++++++++
+ 4 files changed, 36 insertions(+)
+
+diff --git a/src/llama-arch.cpp b/src/llama-arch.cpp
+index b6f20286..b443fcd3 100644
+--- a/src/llama-arch.cpp
++++ b/src/llama-arch.cpp
+@@ -37,6 +37,7 @@ static const std::map<llm_arch, const char *> LLM_ARCH_NAMES = {
+     { LLM_ARCH_MINICPM3,         "minicpm3"         },
+     { LLM_ARCH_GEMMA,            "gemma"            },
+     { LLM_ARCH_GEMMA2,           "gemma2"           },
++    { LLM_ARCH_GEMMA3,           "gemma3"           },
+     { LLM_ARCH_STARCODER2,       "starcoder2"       },
+     { LLM_ARCH_MAMBA,            "mamba"            },
+     { LLM_ARCH_XVERSE,           "xverse"           },
+@@ -804,6 +805,24 @@ static const std::map<llm_arch, std::map<llm_tensor, const char *>> LLM_TENSOR_N
+             { LLM_TENSOR_FFN_POST_NORM,   "blk.%d.post_ffw_norm" },
+         },
+     },
++    {
++        LLM_ARCH_GEMMA3,
++        {
++            { LLM_TENSOR_TOKEN_EMBD,      "token_embd" },
++            { LLM_TENSOR_OUTPUT_NORM,     "output_norm" },
++            { LLM_TENSOR_ATTN_NORM,       "blk.%d.attn_norm" },
++            { LLM_TENSOR_ATTN_Q,          "blk.%d.attn_q" },
++            { LLM_TENSOR_ATTN_K,          "blk.%d.attn_k" },
++            { LLM_TENSOR_ATTN_V,          "blk.%d.attn_v" },
++            { LLM_TENSOR_ATTN_OUT,        "blk.%d.attn_output" },
++            { LLM_TENSOR_ATTN_POST_NORM,  "blk.%d.post_attention_norm" },
++            { LLM_TENSOR_FFN_NORM,        "blk.%d.ffn_norm" },
++            { LLM_TENSOR_FFN_GATE,        "blk.%d.ffn_gate" },
++            { LLM_TENSOR_FFN_DOWN,        "blk.%d.ffn_down" },
++            { LLM_TENSOR_FFN_UP,          "blk.%d.ffn_up" },
++            { LLM_TENSOR_FFN_POST_NORM,   "blk.%d.post_ffw_norm" },
++        },
++    },
+     {
+         LLM_ARCH_STARCODER2,
+         {
+diff --git a/src/llama-arch.h b/src/llama-arch.h
+index ec742224..aad92a5d 100644
+--- a/src/llama-arch.h
++++ b/src/llama-arch.h
+@@ -41,6 +41,7 @@ enum llm_arch {
+     LLM_ARCH_MINICPM3,
+     LLM_ARCH_GEMMA,
+     LLM_ARCH_GEMMA2,
++    LLM_ARCH_GEMMA3,
+     LLM_ARCH_STARCODER2,
+     LLM_ARCH_MAMBA,
+     LLM_ARCH_XVERSE,
+diff --git a/src/llama-model.cpp b/src/llama-model.cpp
+index ab1a07d1..70183041 100644
+--- a/src/llama-model.cpp
++++ b/src/llama-model.cpp
+@@ -878,6 +878,9 @@ void llama_model::load_hparams(llama_model_loader & ml) {
+                     default: type = LLM_TYPE_UNKNOWN;
+                }
+             } break;
++        case LLM_ARCH_GEMMA3:
++            {
++            } break;
+         case LLM_ARCH_STARCODER2:
+             {
+                 ml.get_key(LLM_KV_ATTENTION_LAYERNORM_EPS, hparams.f_norm_eps);
+@@ -2537,6 +2540,9 @@ bool llama_model::load_tensors(llama_model_loader & ml) {
+                         layer.ffn_post_norm = create_tensor(tn(LLM_TENSOR_FFN_POST_NORM, "weight", i), {n_embd}, 0);
+                     }
+                 } break;
++            case LLM_ARCH_GEMMA3:
++                {
++                } break;
+             case LLM_ARCH_STARCODER2:
+                 {
+                     tok_embd = create_tensor(tn(LLM_TENSOR_TOKEN_EMBD, "weight"), {n_embd, n_vocab}, 0);
+@@ -4029,6 +4035,7 @@ enum llama_rope_type llama_model_rope_type(const struct llama_model * model) {
+         case LLM_ARCH_PHIMOE:
+         case LLM_ARCH_GEMMA:
+         case LLM_ARCH_GEMMA2:
++        case LLM_ARCH_GEMMA3:
+         case LLM_ARCH_STARCODER2:
+         case LLM_ARCH_OPENELM:
+         case LLM_ARCH_GPTNEOX:
+diff --git a/src/llama-quant.cpp b/src/llama-quant.cpp
+index 6eb1da08..d2f3a510 100644
+--- a/src/llama-quant.cpp
++++ b/src/llama-quant.cpp
+@@ -737,6 +737,15 @@ static void llama_model_quantize_impl(const std::string & fname_inp, const std::
+         // This used to be a regex, but <regex> has an extreme cost to compile times.
+         bool quantize = name.rfind("weight") == name.size() - 6; // ends with 'weight'?
+ 
++        // don't quantize vision stuff
++        quantize &= name.find("v.blk.") == std::string::npos;
++
++        quantize &= name.find("mm.mm_input_projection.weight") == std::string::npos;
++        quantize &= name.find("mm.mm_soft_emb_norm.weight") == std::string::npos;
++        quantize &= name.find("v.patch_embedding.weight") == std::string::npos;
++        quantize &= name.find("v.position_embedding.weight") == std::string::npos;
++        quantize &= name.find("v.post_layernorm.weight") == std::string::npos;
++
+         // quantize only 2D and 3D tensors (experts)
+         quantize &= (ggml_n_dims(tensor) >= 2);
+ 

llama/patches/0022-add-rdna4-support.patch

@@ -0,0 +1,103 @@
+From 0000000000000000000000000000000000000000 Mon Sep 17 00:00:00 2001
+From: Saman <saman.khatir@amd.com>
+Date: Wed, 19 Mar 2025 14:02:26 -0700
+Subject: [PATCH] add rdna4 support
+
+---
+ ggml/src/ggml-cuda/common.cuh    | 6 ++++--
+ ggml/src/ggml-cuda/mmq.cu        | 2 +-
+ ggml/src/ggml-cuda/mmq.cuh       | 4 ++--
+ ggml/src/ggml-cuda/mmvq.cu       | 4 ++--
+ ggml/src/ggml-cuda/vendors/hip.h | 4 ++++
+ 5 files changed, 13 insertions(+), 7 deletions(-)
+
+diff --git a/ggml/src/ggml-cuda/common.cuh b/ggml/src/ggml-cuda/common.cuh
+index adf0d3ec..b24593fc 100644
+--- a/ggml/src/ggml-cuda/common.cuh
++++ b/ggml/src/ggml-cuda/common.cuh
+@@ -61,11 +61,13 @@
+ #define GGML_CUDA_CC_RDNA1      (GGML_CUDA_CC_OFFSET_AMD + 0x1010) // RX 5000
+ #define GGML_CUDA_CC_RDNA2      (GGML_CUDA_CC_OFFSET_AMD + 0x1030) // RX 6000, minimum for dp4a
+ #define GGML_CUDA_CC_RDNA3      (GGML_CUDA_CC_OFFSET_AMD + 0x1100) // RX 7000, minimum for WMMA
++#define GGML_CUDA_CC_RDNA4      (GGML_CUDA_CC_OFFSET_AMD + 0x1200) // RX 9000
+ 
+ #define GGML_CUDA_CC_IS_RDNA(cc)  (cc >= GGML_CUDA_CC_RDNA1)
+ #define GGML_CUDA_CC_IS_RDNA1(cc) (cc >= GGML_CUDA_CC_RDNA1 && cc < GGML_CUDA_CC_RDNA2)
+ #define GGML_CUDA_CC_IS_RDNA2(cc) (cc >= GGML_CUDA_CC_RDNA2 && cc < GGML_CUDA_CC_RDNA3)
+-#define GGML_CUDA_CC_IS_RDNA3(cc) (cc >= GGML_CUDA_CC_RDNA3)
++#define GGML_CUDA_CC_IS_RDNA3(cc) (cc >= GGML_CUDA_CC_RDNA3 && cc < GGML_CUDA_CC_RDNA4)
++#define GGML_CUDA_CC_IS_RDNA4(cc) (cc >= GGML_CUDA_CC_RDNA4)
+ #define GGML_CUDA_CC_IS_GCN(cc)   (cc > GGML_CUDA_CC_OFFSET_AMD && cc < GGML_CUDA_CC_CDNA)
+ #define GGML_CUDA_CC_IS_CDNA(cc)  (cc >= GGML_CUDA_CC_CDNA && cc < GGML_CUDA_CC_RDNA1)
+ 
+@@ -386,7 +388,7 @@ static __device__ __forceinline__ int ggml_cuda_dp4a(const int a, const int b, i
+ #if defined(GGML_USE_HIP) && defined(__HIP_PLATFORM_AMD__)
+ #if defined(__gfx906__) || defined(__gfx908__) || defined(__gfx90a__) || defined(RDNA2)
+     c = __builtin_amdgcn_sdot4(a, b, c, false);
+-#elif defined(RDNA3)
++#elif defined(RDNA3) || defined(RDNA4)
+     c = __builtin_amdgcn_sudot4( true, a, true, b, c, false);
+ #elif defined(__gfx1010__) || defined(__gfx900__)
+     int tmp1;
+diff --git a/ggml/src/ggml-cuda/mmq.cu b/ggml/src/ggml-cuda/mmq.cu
+index 10f2ebb1..933d945c 100644
+--- a/ggml/src/ggml-cuda/mmq.cu
++++ b/ggml/src/ggml-cuda/mmq.cu
+@@ -149,5 +149,5 @@ bool ggml_cuda_should_use_mmq(enum ggml_type type, int cc, int64_t ne11) {
+         return !fp16_mma_hardware_available(cc) || ne11 < MMQ_DP4A_MAX_BATCH_SIZE;
+     }
+ 
+-    return (!GGML_CUDA_CC_IS_RDNA3(cc) && !GGML_CUDA_CC_IS_CDNA(cc)) || ne11 < MMQ_DP4A_MAX_BATCH_SIZE;
++    return (!GGML_CUDA_CC_IS_RDNA4(cc) && !GGML_CUDA_CC_IS_RDNA3(cc) && !GGML_CUDA_CC_IS_CDNA(cc)) || ne11 < MMQ_DP4A_MAX_BATCH_SIZE;
+ }
+diff --git a/ggml/src/ggml-cuda/mmq.cuh b/ggml/src/ggml-cuda/mmq.cuh
+index 0451c65f..66ce2bc9 100644
+--- a/ggml/src/ggml-cuda/mmq.cuh
++++ b/ggml/src/ggml-cuda/mmq.cuh
+@@ -2577,9 +2577,9 @@ static __device__ void mul_mat_q_process_tile(
+ 
+ template <ggml_type type, int mmq_x, int nwarps, bool need_check>
+ #if defined(GGML_USE_HIP) && defined(__HIP_PLATFORM_AMD__)
+-#if defined(RDNA3) || defined(RDNA2) || defined(CDNA) || defined(GCN)
++#if defined(RDNA4) || defined(RDNA3) || defined(RDNA2) || defined(CDNA) || defined(GCN)
+     __launch_bounds__(WARP_SIZE*nwarps, 2)
+-#endif // defined(RDNA3) || defined(RDNA2) || defined(CDNA) || defined(GCN)
++#endif // defined(RDNA4) || defined(RDNA3) || defined(RDNA2) || defined(CDNA) || defined(GCN)
+ #else
+ #if __CUDA_ARCH__ >= GGML_CUDA_CC_VOLTA
+     __launch_bounds__(WARP_SIZE*nwarps, 1)
+diff --git a/ggml/src/ggml-cuda/mmvq.cu b/ggml/src/ggml-cuda/mmvq.cu
+index 4fb466ca..23ae7abc 100644
+--- a/ggml/src/ggml-cuda/mmvq.cu
++++ b/ggml/src/ggml-cuda/mmvq.cu
+@@ -62,13 +62,13 @@ static __global__ void mul_mat_vec_q(
+ 
+     constexpr vec_dot_q_cuda_t vec_dot_q_cuda = get_vec_dot_q_cuda(type);
+ 
+-#if defined(GGML_USE_HIP) && defined(__HIP_PLATFORM_AMD__) && (defined(RDNA2) || defined(RDNA3))
++#if defined(GGML_USE_HIP) && defined(__HIP_PLATFORM_AMD__) && (defined(RDNA2) || defined(RDNA3) || defined(RDNA4))
+     constexpr int nwarps              = 1;
+     constexpr int rows_per_cuda_block = 1;
+ #else
+     constexpr int nwarps              = ncols_y <= 4 ? 4 : 2;
+     constexpr int rows_per_cuda_block = ncols_y == 1 ? 1 : 2;
+-#endif // defined(GGML_USE_HIP) && defined(__HIP_PLATFORM_AMD__) && !defined(RDNA2) && !defined(RDNA3)
++#endif // defined(GGML_USE_HIP) && defined(__HIP_PLATFORM_AMD__) && !defined(RDNA2) && !defined(RDNA3) && !defined(RDNA4)
+ 
+     const     int tid = WARP_SIZE*threadIdx.y + threadIdx.x;
+     const     int row0 = rows_per_cuda_block*blockIdx.x;
+diff --git a/ggml/src/ggml-cuda/vendors/hip.h b/ggml/src/ggml-cuda/vendors/hip.h
+index 81964611..a62544b5 100644
+--- a/ggml/src/ggml-cuda/vendors/hip.h
++++ b/ggml/src/ggml-cuda/vendors/hip.h
+@@ -150,6 +150,10 @@
+ #define CDNA
+ #endif
+ 
++#if defined(__gfx1200__) || defined(__gfx1201__)
++#define RDNA4
++#endif
++
+ #if defined(__gfx1100__) || defined(__gfx1101__) || defined(__gfx1102__) || defined(__gfx1103__) || \
+     defined(__gfx1150__) || defined(__gfx1151__)
+ #define RDNA3

llm/memory.go

@@ -15,12 +15,12 @@ import (
 )
 
 // This algorithm looks for a complete fit to determine if we need to unload other models
-func PredictServerFit(allGpus discover.GpuInfoList, f *ggml.GGML, adapters, projectors []string, opts api.Options) (bool, uint64) {
+func PredictServerFit(allGpus discover.GpuInfoList, f *ggml.GGML, adapters, projectors []string, opts api.Options, numParallel int) (bool, uint64) {
 	// Split up the GPUs by type and try them
 	var estimatedVRAM uint64
 	for _, gpus := range allGpus.ByLibrary() {
 		var layerCount int
-		estimate := EstimateGPULayers(gpus, f, projectors, opts)
+		estimate := EstimateGPULayers(gpus, f, projectors, opts, numParallel)
 		layerCount, estimatedVRAM = estimate.Layers, estimate.VRAMSize
 		if opts.NumGPU < 0 {
 			if layerCount > 0 && layerCount >= int(f.KV().BlockCount()+1) {
@@ -71,7 +71,7 @@ type MemoryEstimate struct {
 
 // Given a model and one or more GPU targets, predict how many layers and bytes we can load, and the total size
 // The GPUs provided must all be the same Library
-func EstimateGPULayers(gpus []discover.GpuInfo, f *ggml.GGML, projectors []string, opts api.Options) MemoryEstimate {
+func EstimateGPULayers(gpus []discover.GpuInfo, f *ggml.GGML, projectors []string, opts api.Options, numParallel int) MemoryEstimate {
 	// Graph size for a partial offload, applies to all GPUs
 	var graphPartialOffload uint64
 
@@ -137,13 +137,19 @@ func EstimateGPULayers(gpus []discover.GpuInfo, f *ggml.GGML, projectors []strin
 		}
 	}
 
-	kv, graphPartialOffload, graphFullOffload := f.GraphSize(uint64(opts.NumCtx), uint64(min(opts.NumCtx, opts.NumBatch)), kvct)
+	kv, graphPartialOffload, graphFullOffload := f.GraphSize(uint64(opts.NumCtx), uint64(min(opts.NumCtx, opts.NumBatch)), numParallel, kvct)
 
-	// KV is proportional to the number of layers
-	layerSize += kv / f.KV().BlockCount()
+	if len(kv) > 0 {
+		layerSize += kv[0]
+	}
+
+	var kvTotal uint64
+	for _, kvLayer := range kv {
+		kvTotal += kvLayer
+	}
 
 	if graphPartialOffload == 0 {
-		graphPartialOffload = f.KV().GQA() * kv / 6
+		graphPartialOffload = f.KV().GQA() * kvTotal / 6
 	}
 	if graphFullOffload == 0 {
 		graphFullOffload = graphPartialOffload
@@ -217,7 +223,7 @@ func EstimateGPULayers(gpus []discover.GpuInfo, f *ggml.GGML, projectors []strin
 		// Some models have inconsistent layer sizes
 		if blk, ok := layers[fmt.Sprintf("blk.%d", i)]; ok {
 			layerSize = blk.Size()
-			layerSize += kv / f.KV().BlockCount()
+			layerSize += kv[i]
 			memoryWeights += blk.Size()
 		}
 
@@ -315,7 +321,7 @@ func EstimateGPULayers(gpus []discover.GpuInfo, f *ggml.GGML, projectors []strin
 		layersRequested:     opts.NumGPU,
 		layersModel:         int(f.KV().BlockCount()) + 1,
 		availableList:       availableList,
-		kv:                  kv,
+		kv:                  kvTotal,
 		allocationsList:     allocationsList,
 		memoryWeights:       memoryWeights,
 		memoryLayerOutput:   memoryLayerOutput,
@@ -374,7 +380,7 @@ func (m MemoryEstimate) LogValue() slog.Value {
 			slog.Group(
 				"weights",
 				// memory of the weights
-				"total", format.HumanBytes2(m.memoryWeights),
+				"total", format.HumanBytes2(m.memoryWeights+m.memoryLayerOutput),
 				// memory of repeating layers
 				"repeating", format.HumanBytes2(m.memoryWeights),
 				// memory of non-repeating layers

llm/memory_test.go

@@ -61,7 +61,7 @@ func TestEstimateGPULayers(t *testing.T) {
 	projectors := []string{}
 	opts := api.DefaultOptions()
 	t.Run("cpu", func(t *testing.T) {
-		estimate := EstimateGPULayers(gpus, ggml, projectors, opts)
+		estimate := EstimateGPULayers(gpus, ggml, projectors, opts, 1)
 		assert.Equal(t, 0, estimate.Layers)
 		assert.Equal(t, uint64(0), estimate.Graph)
 	})
@@ -112,7 +112,7 @@ func TestEstimateGPULayers(t *testing.T) {
 			gpus[1].FreeMemory += gpuMinimumMemory + layerSize + s.layer1*layerSize + 1
 			gpus[0].FreeMemory += max(graphFullOffload, graphPartialOffload)
 			gpus[1].FreeMemory += max(graphFullOffload, graphPartialOffload)
-			estimate := EstimateGPULayers(gpus, ggml, projectors, opts)
+			estimate := EstimateGPULayers(gpus, ggml, projectors, opts, 1)
 			assert.Equal(t, int(s.expect0+s.expect1), estimate.Layers, "scenario %d: %v", i, s)
 			assert.Equal(t, fmt.Sprintf("%d,%d", s.expect0, s.expect1), estimate.TensorSplit, "scenario %d: %v", i, s)
 			var layerSums uint64

llm/server.go

@@ -109,7 +109,7 @@ func NewLlamaServer(gpus discover.GpuInfoList, modelPath string, f *ggml.GGML, a
 		gpus = discover.GetCPUInfo()
 	}
 
-	estimate := EstimateGPULayers(gpus, f, projectors, opts)
+	estimate := EstimateGPULayers(gpus, f, projectors, opts, numParallel)
 	if len(gpus) > 1 || gpus[0].Library != "cpu" {
 		switch {
 		case gpus[0].Library == "metal" && estimate.VRAMSize > systemTotalMemory:
@@ -402,7 +402,7 @@ func NewLlamaServer(gpus discover.GpuInfoList, modelPath string, f *ggml.GGML, a
 			s.cmd.Env = append(s.cmd.Env, visibleDevicesEnv+"="+visibleDevicesEnvVal)
 		}
 
-		slog.Info("starting llama server", "cmd", s.cmd.String())
+		slog.Info("starting llama server", "cmd", s.cmd)
 		if envconfig.Debug() {
 			filteredEnv := []string{}
 			for _, ev := range s.cmd.Env {
@@ -470,7 +470,7 @@ const ( // iota is reset to 0
 	ServerStatusError
 )
 
-func (s ServerStatus) ToString() string {
+func (s ServerStatus) String() string {
 	switch s {
 	case ServerStatusReady:
 		return "llm server ready"
@@ -485,12 +485,9 @@ func (s ServerStatus) ToString() string {
 	}
 }
 
-type ServerStatusResp struct {
-	Status          string  `json:"status"`
-	SlotsIdle       int     `json:"slots_idle"`
-	SlotsProcessing int     `json:"slots_processing"`
-	Error           string  `json:"error"`
-	Progress        float32 `json:"progress"`
+type ServerStatusResponse struct {
+	Status   ServerStatus `json:"status"`
+	Progress float32      `json:"progress"`
 }
 
 func (s *llmServer) getServerStatus(ctx context.Context) (ServerStatus, error) {
@@ -502,7 +499,7 @@ func (s *llmServer) getServerStatus(ctx context.Context) (ServerStatus, error) {
 		}
 		if s.cmd.ProcessState.ExitCode() == -1 {
 			// Most likely a signal killed it, log some more details to try to help troubleshoot
-			slog.Warn("llama runner process no longer running", "sys", s.cmd.ProcessState.Sys(), "string", s.cmd.ProcessState.String())
+			slog.Warn("llama runner process no longer running", "sys", s.cmd.ProcessState.Sys(), "string", s.cmd.ProcessState)
 		}
 		return ServerStatusError, fmt.Errorf("llama runner process no longer running: %d %s", s.cmd.ProcessState.ExitCode(), msg)
 	}
@@ -527,21 +524,19 @@ func (s *llmServer) getServerStatus(ctx context.Context) (ServerStatus, error) {
 		return ServerStatusError, fmt.Errorf("read health request: %w", err)
 	}
 
-	var status ServerStatusResp
-	if err := json.Unmarshal(body, &status); err != nil {
+	var ssr ServerStatusResponse
+	if err := json.Unmarshal(body, &ssr); err != nil {
 		return ServerStatusError, fmt.Errorf("health unmarshal encode response: %w", err)
 	}
 
-	switch status.Status {
-	case "ok":
-		return ServerStatusReady, nil
-	case "no slot available":
-		return ServerStatusNoSlotsAvailable, nil
-	case "loading model":
-		s.loadProgress = status.Progress
-		return ServerStatusLoadingModel, nil
+	switch ssr.Status {
+	case ServerStatusLoadingModel:
+		s.loadProgress = ssr.Progress
+		return ssr.Status, nil
+	case ServerStatusReady, ServerStatusNoSlotsAvailable:
+		return ssr.Status, nil
 	default:
-		return ServerStatusError, fmt.Errorf("server error: %+v", status)
+		return ssr.Status, fmt.Errorf("server error: %+v", ssr)
 	}
 }
 
@@ -616,7 +611,7 @@ func (s *llmServer) WaitUntilRunning(ctx context.Context) error {
 		status, _ := s.getServerStatus(ctx)
 		if lastStatus != status && status != ServerStatusReady {
 			// Only log on status changes
-			slog.Info("waiting for server to become available", "status", status.ToString())
+			slog.Info("waiting for server to become available", "status", status)
 		}
 		switch status {
 		case ServerStatusReady:
@@ -630,7 +625,7 @@ func (s *llmServer) WaitUntilRunning(ctx context.Context) error {
 				slog.Debug(fmt.Sprintf("model load progress %0.2f", s.loadProgress))
 				stallTimer = time.Now().Add(stallDuration)
 			} else if !fullyLoaded && int(s.loadProgress*100.0) >= 100 {
-				slog.Debug("model load completed, waiting for server to become available", "status", status.ToString())
+				slog.Debug("model load completed, waiting for server to become available", "status", status)
 				stallTimer = time.Now().Add(stallDuration)
 				fullyLoaded = true
 			}
@@ -671,63 +666,26 @@ type ImageData struct {
 	AspectRatioID int    `json:"aspect_ratio_id"`
 }
 
-type completion struct {
-	Content      string `json:"content"`
-	Model        string `json:"model"`
-	Prompt       string `json:"prompt"`
-	Stop         bool   `json:"stop"`
-	StoppedLimit bool   `json:"stopped_limit"`
-
-	Timings struct {
-		PredictedN  int     `json:"predicted_n"`
-		PredictedMS float64 `json:"predicted_ms"`
-		PromptN     int     `json:"prompt_n"`
-		PromptMS    float64 `json:"prompt_ms"`
-	}
-}
-
 type CompletionRequest struct {
 	Prompt  string
 	Format  json.RawMessage
 	Images  []ImageData
 	Options *api.Options
+
+	Grammar string // set before sending the request to the subprocess
 }
 
 type CompletionResponse struct {
-	Content            string
-	DoneReason         string
-	Done               bool
-	PromptEvalCount    int
-	PromptEvalDuration time.Duration
-	EvalCount          int
-	EvalDuration       time.Duration
+	Content            string        `json:"content"`
+	DoneReason         string        `json:"done_reason"`
+	Done               bool          `json:"done"`
+	PromptEvalCount    int           `json:"prompt_eval_count"`
+	PromptEvalDuration time.Duration `json:"prompt_eval_duration"`
+	EvalCount          int           `json:"eval_count"`
+	EvalDuration       time.Duration `json:"eval_duration"`
 }
 
 func (s *llmServer) Completion(ctx context.Context, req CompletionRequest, fn func(CompletionResponse)) error {
-	request := map[string]any{
-		"prompt":            req.Prompt,
-		"stream":            true,
-		"n_predict":         req.Options.NumPredict,
-		"n_keep":            req.Options.NumKeep,
-		"main_gpu":          req.Options.MainGPU,
-		"temperature":       req.Options.Temperature,
-		"top_k":             req.Options.TopK,
-		"top_p":             req.Options.TopP,
-		"min_p":             req.Options.MinP,
-		"typical_p":         req.Options.TypicalP,
-		"repeat_last_n":     req.Options.RepeatLastN,
-		"repeat_penalty":    req.Options.RepeatPenalty,
-		"presence_penalty":  req.Options.PresencePenalty,
-		"frequency_penalty": req.Options.FrequencyPenalty,
-		"mirostat":          req.Options.Mirostat,
-		"mirostat_tau":      req.Options.MirostatTau,
-		"mirostat_eta":      req.Options.MirostatEta,
-		"seed":              req.Options.Seed,
-		"stop":              req.Options.Stop,
-		"image_data":        req.Images,
-		"cache_prompt":      true,
-	}
-
 	if len(req.Format) > 0 {
 		switch string(req.Format) {
 		case `null`, `""`:
@@ -735,7 +693,7 @@ func (s *llmServer) Completion(ctx context.Context, req CompletionRequest, fn fu
 			// these as "not set".
 			break
 		case `"json"`:
-			request["grammar"] = grammarJSON
+			req.Grammar = grammarJSON
 		default:
 			if req.Format[0] != '{' {
 				return fmt.Errorf("invalid format: %q; expected \"json\" or a valid JSON Schema object", req.Format)
@@ -746,10 +704,15 @@ func (s *llmServer) Completion(ctx context.Context, req CompletionRequest, fn fu
 			if g == nil {
 				return fmt.Errorf("invalid JSON schema in format")
 			}
-			request["grammar"] = string(g)
+			req.Grammar = string(g)
 		}
 	}
 
+	if req.Options == nil {
+		opts := api.DefaultOptions()
+		req.Options = &opts
+	}
+
 	if err := s.sem.Acquire(ctx, 1); err != nil {
 		if errors.Is(err, context.Canceled) {
 			slog.Info("aborting completion request due to client closing the connection")
@@ -770,7 +733,7 @@ func (s *llmServer) Completion(ctx context.Context, req CompletionRequest, fn fu
 	if err != nil {
 		return err
 	} else if status != ServerStatusReady {
-		return fmt.Errorf("unexpected server status: %s", status.ToString())
+		return fmt.Errorf("unexpected server status: %s", status)
 	}
 
 	// Handling JSON marshaling with special characters unescaped.
@@ -778,7 +741,7 @@ func (s *llmServer) Completion(ctx context.Context, req CompletionRequest, fn fu
 	enc := json.NewEncoder(buffer)
 	enc.SetEscapeHTML(false)
 
-	if err := enc.Encode(request); err != nil {
+	if err := enc.Encode(req); err != nil {
 		return fmt.Errorf("failed to marshal data: %v", err)
 	}
 
@@ -829,7 +792,7 @@ func (s *llmServer) Completion(ctx context.Context, req CompletionRequest, fn fu
 				evt = line
 			}
 
-			var c completion
+			var c CompletionResponse
 			if err := json.Unmarshal(evt, &c); err != nil {
 				return fmt.Errorf("error unmarshalling llm prediction response: %v", err)
 			}
@@ -853,20 +816,8 @@ func (s *llmServer) Completion(ctx context.Context, req CompletionRequest, fn fu
 				})
 			}
 
-			if c.Stop {
-				doneReason := "stop"
-				if c.StoppedLimit {
-					doneReason = "length"
-				}
-
-				fn(CompletionResponse{
-					Done:               true,
-					DoneReason:         doneReason,
-					PromptEvalCount:    c.Timings.PromptN,
-					PromptEvalDuration: parseDurationMs(c.Timings.PromptMS),
-					EvalCount:          c.Timings.PredictedN,
-					EvalDuration:       parseDurationMs(c.Timings.PredictedMS),
-				})
+			if c.Done {
+				fn(c)
 				return nil
 			}
 		}
@@ -914,7 +865,7 @@ func (s *llmServer) Embedding(ctx context.Context, input string) ([]float32, err
 	if err != nil {
 		return nil, err
 	} else if status != ServerStatusReady {
-		return nil, fmt.Errorf("unexpected server status: %s", status.ToString())
+		return nil, fmt.Errorf("unexpected server status: %s", status)
 	}
 
 	data, err := json.Marshal(EmbeddingRequest{Content: input})
@@ -1059,12 +1010,3 @@ func (s *llmServer) EstimatedVRAMByGPU(gpuID string) uint64 {
 	}
 	return 0
 }
-
-func parseDurationMs(ms float64) time.Duration {
-	dur, err := time.ParseDuration(fmt.Sprintf("%fms", ms))
-	if err != nil {
-		panic(err)
-	}
-
-	return dur
-}

ml/backend.go

@@ -2,6 +2,7 @@ package ml
 
 import (
 	"bytes"
+	"context"
 	"encoding/binary"
 	"fmt"
 	"os"
@@ -60,6 +61,10 @@ type CacheConfig struct {
 
 // BackendParams controls how the backend loads and executes models
 type BackendParams struct {
+	// Progress is a callback function that allows reporting percentage completion
+	// of model loading
+	Progress func(float32)
+
 	// NumThreads sets the number of threads to use if running on the CPU
 	NumThreads int
 
@@ -76,9 +81,9 @@ type BackendParams struct {
 	FlashAttention bool
 }
 
-var backends = make(map[string]func(*os.File, BackendParams) (Backend, error))
+var backends = make(map[string]func(context.Context, *os.File, BackendParams) (Backend, error))
 
-func RegisterBackend(name string, f func(*os.File, BackendParams) (Backend, error)) {
+func RegisterBackend(name string, f func(context.Context, *os.File, BackendParams) (Backend, error)) {
 	if _, ok := backends[name]; ok {
 		panic("backend: backend already registered")
 	}
@@ -86,9 +91,9 @@ func RegisterBackend(name string, f func(*os.File, BackendParams) (Backend, erro
 	backends[name] = f
 }
 
-func NewBackend(f *os.File, params BackendParams) (Backend, error) {
+func NewBackend(ctx context.Context, f *os.File, params BackendParams) (Backend, error) {
 	if backend, ok := backends["ggml"]; ok {
-		return backend(f, params)
+		return backend(ctx, f, params)
 	}
 
 	return nil, fmt.Errorf("unsupported backend")
@@ -105,12 +110,10 @@ type Context interface {
 	MaxGraphNodes() int
 	Close()
 
-	// Input returns a context appropriate for creating input tensors
+	// Input returns a context appropriate for creating tensors that are
+	// inputs to the model (which includes things like output locations)
 	Input() Context
 
-	// Output returns a context appropriate for creating output tensors
-	Output() Context
-
 	// Layer returns a context appropriate for creating intermediate tensors
 	Layer(int) Context
 }

ml/backend/ggml/ggml.go

@@ -9,15 +9,17 @@ package ggml
 import "C"
 
 import (
-	"errors"
+	"context"
 	"fmt"
 	"io"
 	"log/slog"
 	"maps"
 	"os"
+	"runtime"
 	"slices"
 	"strconv"
 	"strings"
+	"sync/atomic"
 	"unicode"
 	"unsafe"
 
@@ -46,9 +48,6 @@ type Backend struct {
 	// input is the backend used for inputs
 	input *C.struct_ggml_backend_buffer_type
 
-	// output is the backend used for outputs
-	output *C.struct_ggml_backend_buffer_type
-
 	// layers is the backend used for repeating layers
 	layers map[int]*C.struct_ggml_backend_buffer_type
 
@@ -58,7 +57,7 @@ type Backend struct {
 	maxGraphNodes int
 }
 
-func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
+func New(ctx context.Context, r *os.File, params ml.BackendParams) (ml.Backend, error) {
 	meta, n, err := fs.Decode(r, -1)
 	if err != nil {
 		return nil, err
@@ -297,12 +296,16 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 		}
 	}
 
-	// concurrently read in tensor data. uses a section reader which is safe for concurrent reads
-	sr := io.NewSectionReader(r, int64(meta.Tensors().Offset), n-int64(meta.Tensors().Offset))
-	var g errgroup.Group
+	var doneBytes atomic.Uint64
+	totalBytes := uint64(n) - meta.Tensors().Offset
+
+	g, ctx := errgroup.WithContext(ctx)
+	g.SetLimit(runtime.GOMAXPROCS(0))
 	for _, t := range meta.Tensors().Items() {
-		for _, target := range targets[t.Name] {
-			g.Go(func() error {
+		g.Go(func() error {
+			tts := make([]*C.struct_ggml_tensor, max(1, len(targets[t.Name])))
+			for i := range tts {
+				target := targets[t.Name][i]
 				if target == "" {
 					target = t.Name
 				}
@@ -312,23 +315,44 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 					return fmt.Errorf("unassigned tensor: %s", t.Name)
 				}
 
-				bts := make([]byte, t.Size())
-				n, err := io.ReadFull(io.NewSectionReader(sr, int64(t.Offset), int64(t.Size())), bts)
+				tts[i] = tt
+			}
+
+			sr := io.NewSectionReader(r, int64(meta.Tensors().Offset+t.Offset), int64(t.Size()))
+			bts := make([]byte, 128*format.KibiByte)
+
+			var s uint64
+			for s < t.Size() {
+				n, err := io.ReadFull(sr, bts[:min(len(bts), int(t.Size()-s))])
 				if err != nil {
 					return err
 				}
 
-				if n != len(bts) {
-					return errors.New("short read")
+				for _, tt := range tts {
+					C.ggml_backend_tensor_set(tt, unsafe.Pointer(&bts[0]), C.size_t(s), C.size_t(n))
 				}
 
-				C.ggml_backend_tensor_set(tt, unsafe.Pointer(&bts[0]), 0, C.size_t(t.Size()))
-				return nil
-			})
-		}
+				s += uint64(n)
+
+				if params.Progress != nil {
+					done := doneBytes.Add(uint64(n))
+					params.Progress(float32(done) / float32(totalBytes))
+				}
+			}
+
+			return nil
+		})
 	}
 
-	if g.Wait() != nil {
+	// start a goroutine to cancel the errgroup if the parent context is done
+	go func() {
+		<-ctx.Done()
+		g.Go(func() error {
+			return ctx.Err()
+		})
+	}()
+
+	if err := g.Wait(); err != nil {
 		return nil, err
 	}
 
@@ -371,10 +395,9 @@ func New(r *os.File, params ml.BackendParams) (ml.Backend, error) {
 			(*C.ggml_backend_buffer_type_t)(unsafe.Pointer(&schedBufts[0])),
 			C.int(len(schedBackends)),
 			C.size_t(maxGraphNodes),
-			true,
+			C._Bool(len(gpus) > 1 && slices.Contains(gpus, output.d)),
 		),
-		input:  deviceBufferTypes[input.d],
-		output: deviceBufferTypes[output.d],
+		input: deviceBufferTypes[input.d],
 		layers: func() map[int]*C.struct_ggml_backend_buffer_type {
 			m := make(map[int]*C.struct_ggml_backend_buffer_type)
 			for i, layer := range layers {
@@ -455,19 +478,6 @@ func (c Context) Input() ml.Context {
 	return &c
 }
 
-func (c Context) Output() ml.Context {
-	if c.b.output != nil {
-		return &Context{
-			b:             c.b,
-			ctx:           c.ctx,
-			buft:          c.b.output,
-			maxGraphNodes: c.maxGraphNodes,
-		}
-	}
-
-	return &c
-}
-
 func (c Context) Layer(i int) ml.Context {
 	if buft, ok := c.b.layers[i]; ok {
 		return &Context{

ml/backend/ggml/ggml/src/ggml-cuda/common.cuh

@@ -61,11 +61,13 @@
 #define GGML_CUDA_CC_RDNA1      (GGML_CUDA_CC_OFFSET_AMD + 0x1010) // RX 5000
 #define GGML_CUDA_CC_RDNA2      (GGML_CUDA_CC_OFFSET_AMD + 0x1030) // RX 6000, minimum for dp4a
 #define GGML_CUDA_CC_RDNA3      (GGML_CUDA_CC_OFFSET_AMD + 0x1100) // RX 7000, minimum for WMMA
+#define GGML_CUDA_CC_RDNA4      (GGML_CUDA_CC_OFFSET_AMD + 0x1200) // RX 9000
 
 #define GGML_CUDA_CC_IS_RDNA(cc)  (cc >= GGML_CUDA_CC_RDNA1)
 #define GGML_CUDA_CC_IS_RDNA1(cc) (cc >= GGML_CUDA_CC_RDNA1 && cc < GGML_CUDA_CC_RDNA2)
 #define GGML_CUDA_CC_IS_RDNA2(cc) (cc >= GGML_CUDA_CC_RDNA2 && cc < GGML_CUDA_CC_RDNA3)
-#define GGML_CUDA_CC_IS_RDNA3(cc) (cc >= GGML_CUDA_CC_RDNA3)
+#define GGML_CUDA_CC_IS_RDNA3(cc) (cc >= GGML_CUDA_CC_RDNA3 && cc < GGML_CUDA_CC_RDNA4)
+#define GGML_CUDA_CC_IS_RDNA4(cc) (cc >= GGML_CUDA_CC_RDNA4)
 #define GGML_CUDA_CC_IS_GCN(cc)   (cc > GGML_CUDA_CC_OFFSET_AMD && cc < GGML_CUDA_CC_CDNA)
 #define GGML_CUDA_CC_IS_CDNA(cc)  (cc >= GGML_CUDA_CC_CDNA && cc < GGML_CUDA_CC_RDNA1)
 
@@ -386,7 +388,7 @@ static __device__ __forceinline__ int ggml_cuda_dp4a(const int a, const int b, i
 #if defined(GGML_USE_HIP) && defined(__HIP_PLATFORM_AMD__)
 #if defined(__gfx906__) || defined(__gfx908__) || defined(__gfx90a__) || defined(RDNA2)
     c = __builtin_amdgcn_sdot4(a, b, c, false);
-#elif defined(RDNA3)
+#elif defined(RDNA3) || defined(RDNA4)
     c = __builtin_amdgcn_sudot4( true, a, true, b, c, false);
 #elif defined(__gfx1010__) || defined(__gfx900__)
     int tmp1;

ml/backend/ggml/ggml/src/ggml-cuda/mmq.cu

@@ -149,5 +149,5 @@ bool ggml_cuda_should_use_mmq(enum ggml_type type, int cc, int64_t ne11) {
         return !fp16_mma_hardware_available(cc) || ne11 < MMQ_DP4A_MAX_BATCH_SIZE;
     }
 
-    return (!GGML_CUDA_CC_IS_RDNA3(cc) && !GGML_CUDA_CC_IS_CDNA(cc)) || ne11 < MMQ_DP4A_MAX_BATCH_SIZE;
+    return (!GGML_CUDA_CC_IS_RDNA4(cc) && !GGML_CUDA_CC_IS_RDNA3(cc) && !GGML_CUDA_CC_IS_CDNA(cc)) || ne11 < MMQ_DP4A_MAX_BATCH_SIZE;
 }

ml/backend/ggml/ggml/src/ggml-cuda/mmq.cuh

@@ -2577,9 +2577,9 @@ static __device__ void mul_mat_q_process_tile(
 
 template <ggml_type type, int mmq_x, int nwarps, bool need_check>
 #if defined(GGML_USE_HIP) && defined(__HIP_PLATFORM_AMD__)
-#if defined(RDNA3) || defined(RDNA2) || defined(CDNA) || defined(GCN)
+#if defined(RDNA4) || defined(RDNA3) || defined(RDNA2) || defined(CDNA) || defined(GCN)
     __launch_bounds__(WARP_SIZE*nwarps, 2)
-#endif // defined(RDNA3) || defined(RDNA2) || defined(CDNA) || defined(GCN)
+#endif // defined(RDNA4) || defined(RDNA3) || defined(RDNA2) || defined(CDNA) || defined(GCN)
 #else
 #if __CUDA_ARCH__ >= GGML_CUDA_CC_VOLTA
     __launch_bounds__(WARP_SIZE*nwarps, 1)

ml/backend/ggml/ggml/src/ggml-cuda/mmvq.cu

@@ -62,13 +62,13 @@ static __global__ void mul_mat_vec_q(
 
     constexpr vec_dot_q_cuda_t vec_dot_q_cuda = get_vec_dot_q_cuda(type);
 
-#if defined(GGML_USE_HIP) && defined(__HIP_PLATFORM_AMD__) && (defined(RDNA2) || defined(RDNA3))
+#if defined(GGML_USE_HIP) && defined(__HIP_PLATFORM_AMD__) && (defined(RDNA2) || defined(RDNA3) || defined(RDNA4))
     constexpr int nwarps              = 1;
     constexpr int rows_per_cuda_block = 1;
 #else
     constexpr int nwarps              = ncols_y <= 4 ? 4 : 2;
     constexpr int rows_per_cuda_block = ncols_y == 1 ? 1 : 2;
-#endif // defined(GGML_USE_HIP) && defined(__HIP_PLATFORM_AMD__) && !defined(RDNA2) && !defined(RDNA3)
+#endif // defined(GGML_USE_HIP) && defined(__HIP_PLATFORM_AMD__) && !defined(RDNA2) && !defined(RDNA3) && !defined(RDNA4)
 
     const     int tid = WARP_SIZE*threadIdx.y + threadIdx.x;
     const     int row0 = rows_per_cuda_block*blockIdx.x;

ml/backend/ggml/ggml/src/ggml-cuda/vendors/hip.h

@@ -150,6 +150,10 @@
 #define CDNA
 #endif
 
+#if defined(__gfx1200__) || defined(__gfx1201__)
+#define RDNA4
+#endif
+
 #if defined(__gfx1100__) || defined(__gfx1101__) || defined(__gfx1102__) || defined(__gfx1103__) || \
     defined(__gfx1150__) || defined(__gfx1151__)
 #define RDNA3

model/input/input.go

@@ -1,5 +1,7 @@
 package input
 
+import "github.com/ollama/ollama/ml"
+
 // Input represents one token in the input stream
 type Input struct {
 	// Token is a single element of text.
@@ -15,6 +17,12 @@ type Input struct {
 	// stored in Multimodal, used for caching and comparing
 	// equality.
 	MultimodalHash uint64
+
+	// SameBatch forces the following number of tokens to be processed
+	// in a single batch, breaking and extending batches as needed.
+	// Useful for things like images that must be processed in one
+	// shot.
+	SameBatch int
 }
 
 // MultimodalIndex is a multimodal element (such as an image)
@@ -27,11 +35,24 @@ type MultimodalIndex struct {
 	Multimodal any
 }
 
-// Options contains the inputs for a model forward pass
-type Options struct {
-	Inputs     []int32
+// Batch contains the inputs for a model forward pass
+type Batch struct {
+	// Inputs is the input tokens, including placeholders for multimodal inputs.
+	Inputs ml.Tensor
+
+	// Multimodal is a set of multimodal embeddings previously created by
+	// EncodeMultimodal, along with an index into Inputs. Unused for text-only
+	// models or for batches without multimodal elements.
 	Multimodal []MultimodalIndex
-	Positions  []int32
-	Sequences  []int
-	Outputs    []int32
+
+	// Positions is the position for each Input, relative to its sequence. Equal
+	// in length to Inputs.
+	Positions []int32
+
+	// Sequences is the sequence for each Input. Equal in length to Inputs.
+	Sequences []int
+
+	// Outputs are the set of indicies into Inputs for which output data should
+	// be returned.
+	Outputs []int32
 }

model/model.go

@@ -1,6 +1,7 @@
 package model
 
 import (
+	"context"
 	"errors"
 	"fmt"
 	_ "image/jpeg"
@@ -26,7 +27,7 @@ var ErrNoVisionModel = errors.New("this model is missing data required for image
 
 // Model implements a specific model architecture, defining the forward pass and any model-specific configuration
 type Model interface {
-	Forward(ml.Context, input.Options) (ml.Tensor, error)
+	Forward(ml.Context, input.Batch) (ml.Tensor, error)
 
 	Backend() ml.Backend
 	Config() config
@@ -60,7 +61,7 @@ type MultimodalProcessor interface {
 	// This function is also responsible for updating MultimodalHash for any Multimodal
 	// that is modified to ensure that there is a unique hash value that accurately
 	// represents the contents.
-	PostTokenize(ml.Context, []input.Input) ([]input.Input, error)
+	PostTokenize([]input.Input) ([]input.Input, error)
 }
 
 // Base implements the common fields and methods for all models
@@ -94,14 +95,14 @@ func Register(name string, f func(ml.Config) (Model, error)) {
 }
 
 // New initializes a new model instance with the provided configuration based on the metadata in the model file
-func New(modelPath string, params ml.BackendParams) (Model, error) {
+func New(ctx context.Context, modelPath string, params ml.BackendParams) (Model, error) {
 	r, err := os.Open(modelPath)
 	if err != nil {
 		return nil, err
 	}
 	defer r.Close()
 
-	b, err := ml.NewBackend(r, params)
+	b, err := ml.NewBackend(ctx, r, params)
 	if err != nil {
 		return nil, err
 	}
@@ -280,24 +281,30 @@ func canNil(t reflect.Type) bool {
 		t.Kind() == reflect.Slice
 }
 
-func Forward(ctx ml.Context, m Model, opts input.Options) (ml.Tensor, error) {
-	if len(opts.Positions) != len(opts.Sequences) {
-		return nil, fmt.Errorf("length of positions (%v) must match length of seqs (%v)", len(opts.Positions), len(opts.Sequences))
+func Forward(ctx ml.Context, m Model, inputs []int32, batch input.Batch) (ml.Tensor, error) {
+	if len(batch.Positions) != len(batch.Sequences) {
+		return nil, fmt.Errorf("length of positions (%v) must match length of seqs (%v)", len(batch.Positions), len(batch.Sequences))
 	}
 
-	if len(opts.Positions) < 1 {
+	if len(batch.Positions) < 1 {
 		return nil, errors.New("batch size cannot be less than 1")
 	}
 
+	var err error
+	batch.Inputs, err = ctx.Input().FromIntSlice(inputs, len(inputs))
+	if err != nil {
+		return nil, err
+	}
+
 	cache := m.Config().Cache
 	if cache != nil {
-		err := cache.StartForward(ctx, opts)
+		err := cache.StartForward(ctx, batch)
 		if err != nil {
 			return nil, err
 		}
 	}
 
-	t, err := m.Forward(ctx, opts)
+	t, err := m.Forward(ctx, batch)
 	if err != nil {
 		return nil, err
 	}

model/model_test.go

@@ -163,7 +163,7 @@ func TestGetTextProcessor(t *testing.T) {
 
 type notTextProcessorModel struct{}
 
-func (notTextProcessorModel) Forward(ml.Context, input.Options) (ml.Tensor, error) {
+func (notTextProcessorModel) Forward(ml.Context, input.Batch) (ml.Tensor, error) {
 	panic("unimplemented")
 }
 

model/models/gemma2/model.go

@@ -38,7 +38,6 @@ const (
 func New(c ml.Config) (model.Model, error) {
 	m := Model{
 		SentencePieceModel: model.NewSentencePieceModel(
-			c.String("tokenizer.ggml.pretokenizer", `(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}{1,3}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+`),
 			&model.Vocabulary{
 				Values: c.Strings("tokenizer.ggml.tokens"),
 				Scores: c.Floats("tokenizer.ggml.scores"),
@@ -168,23 +167,18 @@ func (l *Layer) Forward(ctx ml.Context, hiddenState, positionIDs, outputs ml.Ten
 	return hiddenState.Add(ctx, residual)
 }
 
-func (m *Model) Forward(ctx ml.Context, opts input.Options) (ml.Tensor, error) {
-	inputs, err := ctx.Input().FromIntSlice(opts.Inputs, len(opts.Inputs))
+func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
+	positions, err := ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions))
 	if err != nil {
 		return nil, err
 	}
 
-	positions, err := ctx.Input().FromIntSlice(opts.Positions, len(opts.Positions))
+	outputs, err := ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs))
 	if err != nil {
 		return nil, err
 	}
 
-	outputs, err := ctx.Output().FromIntSlice(opts.Outputs, len(opts.Outputs))
-	if err != nil {
-		return nil, err
-	}
-
-	hiddenState := m.TokenEmbedding.Forward(ctx, inputs)
+	hiddenState := m.TokenEmbedding.Forward(ctx, batch.Inputs)
 	hiddenState = hiddenState.Scale(ctx, math.Sqrt(float64(m.Options.hiddenSize)))
 
 	if len(m.Layers) == gemma27BLayerCount {
@@ -211,8 +205,7 @@ func (m *Model) Forward(ctx ml.Context, opts input.Options) (ml.Tensor, error) {
 	// final logit softcap
 	hiddenState = hiddenState.Scale(ctx, 1.0/float64(m.Options.finalLogitSoftcap))
 	hiddenState = hiddenState.Tanh(ctx)
-	hiddenState = hiddenState.Scale(ctx, float64(m.Options.finalLogitSoftcap))
-	return hiddenState.Rows(ctx, outputs), nil
+	return hiddenState.Scale(ctx, float64(m.Options.finalLogitSoftcap)), nil
 }
 
 func init() {

model/models/gemma3/model.go

@@ -2,10 +2,9 @@ package gemma3
 
 import (
 	"bytes"
-	"encoding/binary"
-	"hash/fnv"
 	"image"
 	"math"
+	"slices"
 
 	"github.com/ollama/ollama/kvcache"
 	"github.com/ollama/ollama/ml"
@@ -56,7 +55,6 @@ func (p *MultiModalProjector) Forward(ctx ml.Context, visionOutputs ml.Tensor, i
 func New(c ml.Config) (model.Model, error) {
 	m := Model{
 		SentencePieceModel: model.NewSentencePieceModel(
-			c.String("tokenizer.ggml.pretokenizer", `(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}{1,3}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+`),
 			&model.Vocabulary{
 				Values: c.Strings("tokenizer.ggml.tokens"),
 				Scores: c.Floats("tokenizer.ggml.scores"),
@@ -112,36 +110,23 @@ func (m *Model) EncodeMultimodal(ctx ml.Context, multimodalData []byte) (any, er
 	return visionOutputs, nil
 }
 
-type imageToken struct {
-	embedding ml.Tensor
-	index     int
-}
-
-func (m *Model) PostTokenize(ctx ml.Context, inputs []input.Input) ([]input.Input, error) {
+func (m *Model) PostTokenize(inputs []input.Input) ([]input.Input, error) {
 	var result []input.Input
-	fnvHash := fnv.New64a()
 
 	for _, inp := range inputs {
 		if inp.Multimodal == nil {
 			result = append(result, inp)
 		} else {
-			imageInputs := []input.Input{
-				{Token: 108},    // "\n\n"
-				{Token: 255999}, // "<start_of_image>""
-			}
-			result = append(result, imageInputs...)
-
-			// add image embeddings
 			inputMultimodal := inp.Multimodal.(ml.Tensor)
 
-			for i := range inputMultimodal.Dim(1) {
-				fnvHash.Reset()
-				binary.Write(fnvHash, binary.NativeEndian, inp.MultimodalHash)
-				fnvHash.Write([]byte{byte(i)})
+			result = append(result,
+				input.Input{Token: 108, SameBatch: inputMultimodal.Dim(1) + 3},               // "\n\n"
+				input.Input{Token: 255999},                                                   // "<start_of_image>""
+				input.Input{Multimodal: inputMultimodal, MultimodalHash: inp.MultimodalHash}, // image data is on the first placeholder
+			)
 
-				imageToken := imageToken{embedding: inputMultimodal, index: i}
-				result = append(result, input.Input{Multimodal: imageToken, MultimodalHash: fnvHash.Sum64()})
-			}
+			// add image token placeholders
+			result = append(result, slices.Repeat([]input.Input{{Token: 0}}, inputMultimodal.Dim(1)-1)...)
 
 			result = append(result,
 				input.Input{Token: 256000}, // <end_of_image>
@@ -153,23 +138,18 @@ func (m *Model) PostTokenize(ctx ml.Context, inputs []input.Input) ([]input.Inpu
 	return result, nil
 }
 
-func (m *Model) Forward(ctx ml.Context, opts input.Options) (ml.Tensor, error) {
-	inputs, err := ctx.Input().FromIntSlice(opts.Inputs, len(opts.Inputs))
+func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
+	positions, err := ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions))
 	if err != nil {
 		return nil, err
 	}
 
-	positions, err := ctx.Input().FromIntSlice(opts.Positions, len(opts.Positions))
+	outputs, err := ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs))
 	if err != nil {
 		return nil, err
 	}
 
-	outputs, err := ctx.Output().FromIntSlice(opts.Outputs, len(opts.Outputs))
-	if err != nil {
-		return nil, err
-	}
-
-	return m.TextModel.Forward(ctx, inputs, positions, outputs, opts, m.Cache), nil
+	return m.TextModel.Forward(ctx, batch.Inputs, positions, outputs, batch, m.Cache), nil
 }
 
 func init() {

model/models/gemma3/model_text.go

@@ -45,7 +45,6 @@ func newTextModel(c ml.Config) *TextModel {
 
 	m := TextModel{
 		SentencePieceModel: model.NewSentencePieceModel(
-			c.String("tokenizer.ggml.pretokenizer", `(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}{1,3}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+`),
 			&model.Vocabulary{
 				Values: c.Strings("tokenizer.ggml.tokens"),
 				Scores: c.Floats("tokenizer.ggml.scores"),
@@ -171,53 +170,20 @@ func (l *TextLayer) Forward(ctx ml.Context, layer int, hiddenState, positionIDs,
 	return hiddenState.Add(ctx, residual)
 }
 
-func setImageEmbeddings(ctx ml.Context, hiddenState ml.Tensor, multimodal []input.MultimodalIndex) []int {
-	var embedding ml.Tensor
-	var src, dst, length int
-	var except []int
-
-	for _, image := range multimodal {
-		imageToken := image.Multimodal.(imageToken)
-		imageSrc := imageToken.index
-		imageDst := image.Index
-
-		if embedding == nil {
-			embedding = imageToken.embedding
-			src = imageSrc
-			dst = imageDst
-			length = 1
-		} else if embedding == imageToken.embedding && imageSrc+1 == src && imageDst+1 == dst {
-			src = imageSrc
-			dst = imageDst
-			length++
-		} else if embedding == imageToken.embedding && src+length == imageSrc && dst+length == imageDst {
-			length++
-		} else {
-			visionOutputs := embedding.View(ctx, src*embedding.Stride(1), length*embedding.Dim(0))
-			ctx.Forward(visionOutputs.Copy(ctx, hiddenState.View(ctx, dst*hiddenState.Stride(1), length*hiddenState.Dim(0))))
-
-			embedding = imageToken.embedding
-			src = imageSrc
-			dst = imageDst
-			length = 1
-		}
-
-		except = append(except, imageDst)
-	}
-
-	if embedding != nil {
-		visionOutputs := embedding.View(ctx, src*embedding.Stride(1), length*embedding.Dim(0))
-		ctx.Forward(visionOutputs.Copy(ctx, hiddenState.View(ctx, dst*hiddenState.Stride(1), length*hiddenState.Dim(0))))
-	}
-
-	return except
-}
-
-func (m *TextModel) Forward(ctx ml.Context, inputs, positions, outputs ml.Tensor, opts input.Options, cache kvcache.Cache) ml.Tensor {
+func (m *TextModel) Forward(ctx ml.Context, inputs, positions, outputs ml.Tensor, batch input.Batch, cache kvcache.Cache) ml.Tensor {
 	hiddenState := m.TokenEmbedding.Forward(ctx, inputs)
 	hiddenState = hiddenState.Scale(ctx, math.Sqrt(float64(m.TextOptions.hiddenSize)))
 
-	except := setImageEmbeddings(ctx, hiddenState, opts.Multimodal)
+	// set image embeddings
+	var except []int
+	for _, image := range batch.Multimodal {
+		visionOutputs := image.Multimodal.(ml.Tensor)
+		ctx.Forward(visionOutputs.Copy(ctx, hiddenState.View(ctx, image.Index*hiddenState.Stride(1), visionOutputs.Dim(0)*visionOutputs.Dim(1))))
+
+		for i := range visionOutputs.Dim(1) {
+			except = append(except, image.Index+i)
+		}
+	}
 
 	for i, layer := range m.Layers {
 		// gemma alternates between the sliding window (local) and causal (global)

model/models/llama/model.go

@@ -139,23 +139,18 @@ func (l *Layer) Forward(ctx ml.Context, hiddenState, positionIDs, outputs ml.Ten
 	return hiddenState.Add(ctx, residual)
 }
 
-func (m *Model) Forward(ctx ml.Context, opts input.Options) (ml.Tensor, error) {
-	inputs, err := ctx.Input().FromIntSlice(opts.Inputs, len(opts.Inputs))
+func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
+	positions, err := ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions))
 	if err != nil {
 		return nil, err
 	}
 
-	positions, err := ctx.Input().FromIntSlice(opts.Positions, len(opts.Positions))
+	outputs, err := ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs))
 	if err != nil {
 		return nil, err
 	}
 
-	outputs, err := ctx.Output().FromIntSlice(opts.Outputs, len(opts.Outputs))
-	if err != nil {
-		return nil, err
-	}
-
-	hiddenState := m.TokenEmbedding.Forward(ctx, inputs)
+	hiddenState := m.TokenEmbedding.Forward(ctx, batch.Inputs)
 
 	for i, layer := range m.Layers {
 		m.Cache.SetLayer(i)

model/models/mllama/model.go

@@ -106,17 +106,17 @@ func (m *Model) EncodeMultimodal(ctx ml.Context, multimodalData []byte) (any, er
 	return m.Projector.Forward(ctx, crossAttentionStates), nil
 }
 
-func (m *Model) PostTokenize(ctx ml.Context, inputs []input.Input) ([]input.Input, error) {
+func (m *Model) PostTokenize(inputs []input.Input) ([]input.Input, error) {
 	var images []input.Input
 	fnvHash := fnv.New64a()
 
 	for i := range inputs {
 		if inputs[i].Multimodal == nil {
 			if len(images) > 0 {
-				inputs[i].Multimodal = images[0].Multimodal
+				inputs[i].Multimodal = []ml.Tensor{images[0].Multimodal.(ml.Tensor)}
 				inputs[i].MultimodalHash = images[0].MultimodalHash
 				for j := 1; j < len(images); j++ {
-					inputs[i].Multimodal = inputs[i].Multimodal.(ml.Tensor).Concat(ctx, images[j].Multimodal.(ml.Tensor), 3)
+					inputs[i].Multimodal = append(inputs[i].Multimodal.([]ml.Tensor), images[0].Multimodal.(ml.Tensor))
 					fnvHash.Reset()
 					binary.Write(fnvHash, binary.NativeEndian, inputs[i].MultimodalHash)
 					binary.Write(fnvHash, binary.NativeEndian, inputs[j].MultimodalHash)
@@ -135,29 +135,27 @@ func (m *Model) PostTokenize(ctx ml.Context, inputs []input.Input) ([]input.Inpu
 	return inputs, nil
 }
 
-func (m *Model) Forward(ctx ml.Context, opts input.Options) (ml.Tensor, error) {
+func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
 	var crossAttentionStates ml.Tensor
-	if len(opts.Multimodal) > 0 {
-		crossAttentionStates = opts.Multimodal[len(opts.Multimodal)-1].Multimodal.(ml.Tensor)
+	if len(batch.Multimodal) > 0 {
+		images := batch.Multimodal[len(batch.Multimodal)-1].Multimodal.([]ml.Tensor)
+		if len(images) > 0 {
+			crossAttentionStates = images[len(images)-1]
+		}
 	}
 
-	inputs, err := ctx.Input().FromIntSlice(opts.Inputs, len(opts.Inputs))
+	positions, err := ctx.Input().FromIntSlice(batch.Positions, len(batch.Positions))
 	if err != nil {
 		return nil, err
 	}
 
-	positions, err := ctx.Input().FromIntSlice(opts.Positions, len(opts.Positions))
-	if err != nil {
-		return nil, err
-	}
-
-	outputs, err := ctx.Output().FromIntSlice(opts.Outputs, len(opts.Outputs))
+	outputs, err := ctx.Input().FromIntSlice(batch.Outputs, len(batch.Outputs))
 	if err != nil {
 		return nil, err
 	}
 
 	// TODO: attention mask, cross attention mask
-	return m.TextModel.Forward(ctx, inputs, positions, outputs, nil, crossAttentionStates, nil, m.Cache.(*kvcache.WrapperCache)), nil
+	return m.TextModel.Forward(ctx, batch.Inputs, positions, outputs, nil, crossAttentionStates, nil, m.Cache.(*kvcache.WrapperCache)), nil
 }
 
 func init() {

model/process_text_spm.go

@@ -1,29 +1,23 @@
 package model
 
 import (
-	"iter"
+	"container/heap"
+	"fmt"
 	"log/slog"
+	"strconv"
 	"strings"
-
-	"github.com/dlclark/regexp2"
-	queue "github.com/emirpasic/gods/v2/queues/priorityqueue"
 )
 
 const spmWhitespaceSep = "▁"
 
-func replaceWhitespaceBySeperator(s string) string {
-	return strings.ReplaceAll(s, " ", spmWhitespaceSep)
-}
-
 type SentencePieceModel struct {
 	maxTokenLen int
-	pre         *regexp2.Regexp
 	vocab       *Vocabulary
 }
 
 var _ TextProcessor = (*SentencePieceModel)(nil)
 
-func NewSentencePieceModel(pre string, vocab *Vocabulary) SentencePieceModel {
+func NewSentencePieceModel(vocab *Vocabulary) SentencePieceModel {
 	slog.Debug("Tokens", "num tokens", len(vocab.Values), "vals", vocab.Values[:5], "scores", vocab.Scores[:5], "types", vocab.Types[:5])
 
 	counter := map[int]int{}
@@ -44,7 +38,6 @@ func NewSentencePieceModel(pre string, vocab *Vocabulary) SentencePieceModel {
 
 	return SentencePieceModel{
 		maxTokenLen: maxTokenLen,
-		pre:         regexp2.MustCompile(pre, regexp2.Unicode|regexp2.RE2),
 		vocab:       vocab,
 	}
 }
@@ -53,20 +46,9 @@ func (spm SentencePieceModel) Is(id int32, special Special) bool {
 	return spm.vocab.Is(id, special)
 }
 
-func (spm *SentencePieceModel) split(s string) iter.Seq[string] {
-	return func(yield func(string) bool) {
-		for m, _ := spm.pre.FindStringMatch(s); m != nil; m, _ = spm.pre.FindNextMatch(m) {
-			if !yield(m.String()) {
-				break
-			}
-		}
-	}
-}
-
 func (spm SentencePieceModel) Encode(s string, addSpecial bool) ([]int32, error) {
 	fragments := []fragment{{value: s}}
 	for _, special := range spm.vocab.SpecialVocabulary() {
-		// TODO: process special tokens concurrently
 		id := spm.vocab.Encode(special)
 		for i := 0; i < len(fragments); i++ {
 			frag := fragments[i]
@@ -91,7 +73,6 @@ func (spm SentencePieceModel) Encode(s string, addSpecial bool) ([]int32, error)
 			fragments = append(fragments[:i], append(middle, fragments[i+1:]...)...)
 		}
 	}
-	slog.Debug("fragments", "frags", fragments)
 
 	var ids []int32
 	for _, frag := range fragments {
@@ -100,105 +81,96 @@ func (spm SentencePieceModel) Encode(s string, addSpecial bool) ([]int32, error)
 			continue
 		}
 
-		for split := range spm.split(frag.value) {
-			split = replaceWhitespaceBySeperator(split)
+		text := strings.ReplaceAll(frag.value, " ", spmWhitespaceSep)
 
-			var sb strings.Builder
-			sb.Write([]byte(split))
-			if id := spm.vocab.Encode(sb.String()); id >= 0 {
-				ids = append(ids, id)
-				continue
+		if id := spm.vocab.Encode(text); id >= 0 {
+			ids = append(ids, id)
+			continue
+		}
+
+		q := &queue{}
+		heap.Init(q)
+
+		runes := []rune(text)
+		merges := make([]merge, len(runes))
+		for r := range runes {
+			merges[r] = merge{
+				p:     r - 1,
+				n:     r + 1,
+				runes: []rune{runes[r]},
 			}
+		}
 
-			runes := []rune(sb.String())
-			pq := queue.NewWith(func(a, b any) int {
-				priA := a.(*candidate)
-				priB := b.(*candidate)
-				if priA.score > priB.score || (priA.score == priB.score && priA.a < priB.a) {
-					return -1
-				}
-				return 1
-			})
-
-			merges := make([]merge, len(runes))
-			for r := range runes {
-				merges[r] = merge{
-					p:     r - 1,
-					n:     r + 1,
-					runes: []rune{runes[r]},
-				}
-			}
-
-			slog.Debug("tokenizer", "merges", merges)
-
-			pairwise := func(a, b int) *candidate {
-				if a < 0 || b >= len(runes) {
-					return nil
-				}
-
-				left, right := string(merges[a].runes), string(merges[b].runes)
-				if id := spm.vocab.Encode(left + right); id >= 0 {
-					return &candidate{
-						a:     a,
-						b:     b,
-						score: spm.vocab.Scores[id],
-					}
-				}
+		pairwise := func(a, b int) *candidate {
+			if a < 0 || b >= len(runes) {
 				return nil
 			}
 
-			for i := range len(runes) - 1 {
-				if pair := pairwise(i, i+1); pair != nil {
-					pq.Enqueue(pair)
+			left, right := string(merges[a].runes), string(merges[b].runes)
+			if id := spm.vocab.Encode(left + right); id >= 0 {
+				return &candidate{
+					a:     a,
+					b:     b,
+					score: spm.vocab.Scores[id],
+					size:  len(left) + len(right),
 				}
 			}
 
-			pqv := pq.Values()
-			for _, v := range pqv {
-				e := v.(*candidate)
-				slog.Debug("candidate", "candidate", e)
+			return nil
+		}
+
+		for i := range len(runes) - 1 {
+			if pair := pairwise(i, i+1); pair != nil {
+				heap.Push(q, pair)
+			}
+		}
+
+		for q.Len() > 0 {
+			pair := heap.Pop(q).(*candidate)
+			left, right := merges[pair.a], merges[pair.b]
+
+			if string(left.runes) == "" || string(right.runes) == "" || len(string(left.runes))+len(string(right.runes)) != pair.size {
+				continue
 			}
 
-			for !pq.Empty() {
-				v, _ := pq.Dequeue()
-				pair := v.(*candidate)
-				left, right := merges[pair.a], merges[pair.b]
+			merges[pair.a].runes = append(left.runes, right.runes...)
+			merges[pair.b].runes = nil
+			merges[pair.a].n = right.n
+			if right.n < len(merges) {
+				merges[right.n].p = pair.a
+			}
 
-				slog.Debug("pair", "left", left, "right", right)
-				if len(left.runes) == 0 || len(right.runes) == 0 {
+			if pair := pairwise(merges[pair.a].p, pair.a); pair != nil {
+				heap.Push(q, pair)
+			}
+
+			if pair := pairwise(pair.a, merges[pair.a].n); pair != nil {
+				heap.Push(q, pair)
+			}
+		}
+
+		for _, merge := range merges {
+			if token := string(merge.runes); token != "" {
+				id := spm.vocab.Encode(token)
+
+				if id >= 0 {
+					ids = append(ids, id)
 					continue
 				}
 
-				if id := spm.vocab.Encode(string(left.runes) + string(right.runes)); id < 0 {
-					continue
-				}
-
-				merges[pair.a].runes = append(left.runes, right.runes...)
-				merges[pair.b].runes = nil
-				merges[pair.a].n = right.n
-				if right.n < len(merges) {
-					merges[right.n].p = pair.a
-				}
-
-				if pair := pairwise(merges[pair.a].p, pair.a); pair != nil {
-					pq.Enqueue(pair)
-				}
-
-				if pair := pairwise(pair.a, merges[pair.a].n); pair != nil {
-					pq.Enqueue(pair)
-				}
-			}
-
-			slog.Debug("merges", "merges", merges)
-
-			for _, merge := range merges {
-				if len(merge.runes) > 0 {
-					if id := spm.vocab.Encode(string(merge.runes)); id >= 0 {
-						ids = append(ids, id)
+				// Fallback to byte tokenization
+				var result []int32
+				for _, b := range []byte(token) {
+					byteToken := fmt.Sprintf("<0x%02X>", b)
+					unknownID := spm.vocab.Encode(byteToken)
+					if unknownID >= 0 {
+						result = append(result, unknownID)
 					} else {
-						slog.Debug("missing token", "token", string(merge.runes))
+						slog.Debug("unknown byte token", "byte", b, "token", byteToken)
 					}
 				}
+
+				ids = append(ids, result...)
 			}
 		}
 	}
@@ -229,6 +201,30 @@ func (spm SentencePieceModel) Encode(s string, addSpecial bool) ([]int32, error)
 type candidate struct {
 	a, b  int
 	score float32
+	size  int
+}
+
+type queue []*candidate
+
+func (q queue) Len() int { return len(q) }
+
+func (q queue) Less(i, j int) bool {
+	return (q[i].score > q[j].score) || (q[i].score == q[j].score && q[i].a < q[j].a)
+}
+
+func (q queue) Swap(i, j int) { q[i], q[j] = q[j], q[i] }
+
+func (q *queue) Push(x interface{}) {
+	item := x.(*candidate)
+	*q = append(*q, item)
+}
+
+func (q *queue) Pop() interface{} {
+	old := *q
+	n := len(old)
+	item := old[n-1]
+	*q = old[0 : n-1]
+	return item
 }
 
 func (spm SentencePieceModel) Decode(ids []int32) (string, error) {
@@ -236,11 +232,26 @@ func (spm SentencePieceModel) Decode(ids []int32) (string, error) {
 	for _, id := range ids {
 		data := spm.vocab.Decode(id)
 		data = strings.ReplaceAll(data, spmWhitespaceSep, " ")
-		if _, err := sb.WriteString(data); err != nil {
-			return "", err
+
+		// For tokenizers that use byte tokens like "<0xEA>"
+		// convert them to the partial unicode character
+		// so they are buffered correctly by the runner instead
+		// of being sent back to the api as "<0xEA>"
+		if len(data) == 6 && strings.HasPrefix(data, "<0x") && strings.HasSuffix(data, ">") {
+			byteVal, err := strconv.ParseUint(data[1:5], 0, 8)
+			if err != nil {
+				return "", fmt.Errorf("failed to parse hex byte: %v", err)
+			}
+
+			if err := sb.WriteByte(byte(byteVal)); err != nil {
+				return "", err
+			}
+		} else {
+			if _, err := sb.WriteString(data); err != nil {
+				return "", err
+			}
 		}
 	}
 
-	slog.Debug("decoded", "ids", ids, "text", sb.String())
 	return sb.String(), nil
 }

model/process_text_spm_test.go

@@ -25,8 +25,6 @@ func loadSentencePieceVocab(t *testing.T) SentencePieceModel {
 		t.Fatal(err)
 	}
 
-	preTokenizer := `(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\r\n\p{L}\p{N}]?\p{L}+|\p{N}{1,3}| ?[^\s\p{L}\p{N}]+[\r\n]*|\s*[\r\n]+|\s+(?!\S)|\s+`
-
 	var v Vocabulary
 
 	for _, piece := range spm.GetPieces() {
@@ -47,7 +45,7 @@ func loadSentencePieceVocab(t *testing.T) SentencePieceModel {
 		}
 	}
 
-	return NewSentencePieceModel(preTokenizer, &v)
+	return NewSentencePieceModel(&v)
 }
 
 func TestSentencePieceEncode(t *testing.T) {
@@ -116,3 +114,59 @@ func TestSentencePieceEncode(t *testing.T) {
 		}
 	})
 }
+
+func TestSentencePieceModelDecodeByteTokens(t *testing.T) {
+	vocab := &Vocabulary{
+		Values: []string{
+			"normal",
+			"<0xEA>",
+			"<0x41>",
+			"<0xC3>",
+			"<0xA3>",
+		},
+		Types: []uint32{
+			TOKEN_TYPE_NORMAL,
+			TOKEN_TYPE_BYTE,
+			TOKEN_TYPE_BYTE,
+			TOKEN_TYPE_BYTE,
+			TOKEN_TYPE_BYTE,
+		},
+		Scores: []float32{0, 0, 0, 0, 0},
+	}
+
+	spm := NewSentencePieceModel(vocab)
+
+	tests := []struct {
+		name     string
+		ids      []int32
+		expected string
+	}{
+		{
+			name:     "single byte token",
+			ids:      []int32{1},
+			expected: "\xea",
+		},
+		{
+			name:     "ASCII byte token",
+			ids:      []int32{2},
+			expected: "A",
+		},
+		{
+			name:     "multiple byte tokens forming UTF-8 character",
+			ids:      []int32{3, 4},
+			expected: "ã",
+		},
+	}
+
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			result, err := spm.Decode(tt.ids)
+			if err != nil {
+				t.Errorf("failed to decode token IDs %v: %v", tt.ids, err)
+			}
+			if result != tt.expected {
+				t.Errorf("got %q, want %q", result, tt.expected)
+			}
+		})
+	}
+}

openai/openai.go

@@ -23,10 +23,10 @@ import (
 var finishReasonToolCalls = "tool_calls"
 
 type Error struct {
-	Message string      `json:"message"`
-	Type    string      `json:"type"`
-	Param   interface{} `json:"param"`
-	Code    *string     `json:"code"`
+	Message string  `json:"message"`
+	Type    string  `json:"type"`
+	Param   any     `json:"param"`
+	Code    *string `json:"code"`
 }
 
 type ErrorResponse struct {
@@ -465,7 +465,7 @@ func fromChatRequest(r ChatCompletionRequest) (*api.ChatRequest, error) {
 		}
 	}
 
-	options := make(map[string]interface{})
+	options := make(map[string]any)
 
 	switch stop := r.Stop.(type) {
 	case string:

openai/openai_test.go

@@ -219,7 +219,7 @@ func TestChatMiddleware(t *testing.T) {
 							{
 								Function: api.ToolCallFunction{
 									Name: "get_current_weather",
-									Arguments: map[string]interface{}{
+									Arguments: map[string]any{
 										"location": "Paris, France",
 										"format":   "celsius",
 									},

runner/llamarunner/cache.go

@@ -213,8 +213,16 @@ func (c *InputCache) ShiftDiscard(inputLen int, numKeep int) int {
 	return discard
 }
 
-// Frees up space in the KV cache by deleting the oldest half of history and shifting
-// the newest half into that space (saving numKeep inputs at the beginning).
+type ErrReprocessInputs struct {
+	Inputs []input
+}
+
+func (e *ErrReprocessInputs) Error() string {
+	return fmt.Sprintf("kv cache shift not supported, inputs need reprocessing (input count: %v)", len(e.Inputs))
+}
+
+// ShiftCacheSlot frees up space in the KV cache by deleting the oldest half of history
+// and shifting the newest half into that space (saving numKeep inputs at the beginning).
 //
 // Assumes that at least 1 entry can be freed up by shifting (i.e. numKeep < numCtx)
 func (c *InputCache) ShiftCacheSlot(slot *InputCacheSlot, numKeep int) error {
@@ -222,7 +230,8 @@ func (c *InputCache) ShiftCacheSlot(slot *InputCacheSlot, numKeep int) error {
 		return fmt.Errorf("unable to shift context - keep exceeds context (keep: %v context: %v)", numKeep, c.numCtx)
 	}
 
-	discard := c.ShiftDiscard(len(slot.Inputs), numKeep)
+	inputLen := len(slot.Inputs)
+	discard := c.ShiftDiscard(inputLen, numKeep)
 
 	if discard <= 0 {
 		return nil
@@ -231,16 +240,42 @@ func (c *InputCache) ShiftCacheSlot(slot *InputCacheSlot, numKeep int) error {
 	slog.Debug("context limit hit - shifting", "id", slot.Id, "limit", c.numCtx, "input", len(slot.Inputs),
 		"keep", numKeep, "discard", discard)
 
-	// TODO (jessegross): KV cache removal can fail for certain types of models
-	if !c.lc.KvCacheSeqRm(slot.Id, numKeep, numKeep+discard) {
-		return fmt.Errorf("unable to remove old kv cache entries (id: %v, keep: %v discard: %v)", slot.Id, numKeep, discard)
-	}
-	c.lc.KvCacheSeqAdd(slot.Id, numKeep+discard, len(slot.Inputs), -discard)
+	var shiftFailed bool
 
-	for i := numKeep + discard; i < len(slot.Inputs); i++ {
+	if c.lc.KvCacheCanShift() {
+		// For models that support shifting, attempt to shift the KV cache
+		if !c.lc.KvCacheSeqRm(slot.Id, numKeep, numKeep+discard) {
+			shiftFailed = true
+			slog.Debug("kv cache removal not supported, clearing cache and returning inputs for reprocessing", "id", slot.Id)
+		} else {
+			c.lc.KvCacheSeqAdd(slot.Id, numKeep+discard, inputLen, -discard)
+		}
+	} else {
+		// For models that don't support shifting
+		shiftFailed = true
+		slog.Debug("kv cache cannot shift, clearing cache and returning inputs for reprocessing", "id", slot.Id)
+	}
+
+	if shiftFailed {
+		// Create new input slice with preserved tokens (numKeep + remaining tokens after discard)
+		newInputs := make([]input, numKeep+inputLen-(numKeep+discard))
+		copy(newInputs[:numKeep], slot.Inputs[:numKeep])
+		copy(newInputs[numKeep:], slot.Inputs[numKeep+discard:])
+
+		// Clear the entire KV cache
+		_ = c.lc.KvCacheSeqRm(slot.Id, 0, -1)
+		// Reset the slot inputs since we've cleared the cache
+		slot.Inputs = []input{}
+
+		// Return error with inputs that need to be reprocessed
+		return &ErrReprocessInputs{Inputs: newInputs}
+	}
+
+	// Standard shift succeeded - update input array
+	for i := numKeep + discard; i < inputLen; i++ {
 		slot.Inputs[i-discard] = slot.Inputs[i]
 	}
-	slot.Inputs = slot.Inputs[:len(slot.Inputs)-discard]
+	slot.Inputs = slot.Inputs[:inputLen-discard]
 
 	return nil
 }

runner/llamarunner/runner.go

@@ -24,6 +24,7 @@ import (
 
 	"github.com/ollama/ollama/api"
 	"github.com/ollama/ollama/llama"
+	"github.com/ollama/ollama/llm"
 	"github.com/ollama/ollama/runner/common"
 )
 
@@ -99,7 +100,7 @@ type NewSequenceParams struct {
 	embedding      bool
 }
 
-func (s *Server) NewSequence(prompt string, images []ImageData, params NewSequenceParams) (*Sequence, error) {
+func (s *Server) NewSequence(prompt string, images []llm.ImageData, params NewSequenceParams) (*Sequence, error) {
 	s.ready.Wait()
 
 	startTime := time.Now()
@@ -163,7 +164,7 @@ func (s *Server) NewSequence(prompt string, images []ImageData, params NewSequen
 // inputs processes the prompt and images into a list of inputs
 // by splitting the prompt on [img-<n>] tags, tokenizing text and
 // generating image embeddings for each image
-func (s *Server) inputs(prompt string, images []ImageData) ([]input, error) {
+func (s *Server) inputs(prompt string, images []llm.ImageData) ([]input, error) {
 	var inputs []input
 	var parts []string
 	var matches [][]string
@@ -229,7 +230,7 @@ type Server struct {
 	image *ImageContext
 
 	// status for external health reporting - loading, ready to serve, etc.
-	status ServerStatus
+	status llm.ServerStatus
 
 	// current progress on loading the model
 	progress float32
@@ -388,7 +389,15 @@ func (s *Server) processBatch(tokenBatch *llama.Batch, embedBatch *llama.Batch)
 				if len(seq.pendingInputs) == 0 {
 					err := s.cache.ShiftCacheSlot(seq.cache, seq.numKeep)
 					if err != nil {
-						return err
+						var reprocess *ErrReprocessInputs
+						if errors.As(err, &reprocess) {
+							// Prepend these inputs to the sequence's inputs queue for reprocessing
+							seq.inputs = append(reprocess.Inputs, seq.inputs...)
+							// Continue processing as normal
+							continue
+						} else {
+							return err
+						}
 					}
 				} else {
 					break
@@ -541,75 +550,18 @@ func (s *Server) processBatch(tokenBatch *llama.Batch, embedBatch *llama.Batch)
 	return nil
 }
 
-// TODO (jmorganca): use structs from the api package to avoid duplication
-// this way the api acts as a proxy instead of using a different api for the
-// runner
-type Options struct {
-	api.Runner
-
-	NumKeep          int      `json:"n_keep"`
-	Seed             int      `json:"seed"`
-	NumPredict       int      `json:"n_predict"`
-	TopK             int      `json:"top_k"`
-	TopP             float32  `json:"top_p"`
-	MinP             float32  `json:"min_p"`
-	TypicalP         float32  `json:"typical_p"`
-	RepeatLastN      int      `json:"repeat_last_n"`
-	Temperature      float32  `json:"temperature"`
-	RepeatPenalty    float32  `json:"repeat_penalty"`
-	PresencePenalty  float32  `json:"presence_penalty"`
-	FrequencyPenalty float32  `json:"frequency_penalty"`
-	Mirostat         int      `json:"mirostat"`
-	MirostatTau      float32  `json:"mirostat_tau"`
-	MirostatEta      float32  `json:"mirostat_eta"`
-	Stop             []string `json:"stop"`
-}
-
-type ImageData struct {
-	Data          []byte `json:"data"`
-	ID            int    `json:"id"`
-	AspectRatioID int    `json:"aspect_ratio_id"`
-}
-
-type CompletionRequest struct {
-	Prompt      string      `json:"prompt"`
-	Images      []ImageData `json:"image_data"`
-	Grammar     string      `json:"grammar"`
-	CachePrompt bool        `json:"cache_prompt"`
-
-	Options
-}
-
-type Timings struct {
-	PredictedN  int     `json:"predicted_n"`
-	PredictedMS float64 `json:"predicted_ms"`
-	PromptN     int     `json:"prompt_n"`
-	PromptMS    float64 `json:"prompt_ms"`
-}
-
-type CompletionResponse struct {
-	Content string `json:"content"`
-	Stop    bool   `json:"stop"`
-
-	Model        string  `json:"model,omitempty"`
-	Prompt       string  `json:"prompt,omitempty"`
-	StoppedLimit bool    `json:"stopped_limit,omitempty"`
-	PredictedN   int     `json:"predicted_n,omitempty"`
-	PredictedMS  float64 `json:"predicted_ms,omitempty"`
-	PromptN      int     `json:"prompt_n,omitempty"`
-	PromptMS     float64 `json:"prompt_ms,omitempty"`
-
-	Timings Timings `json:"timings"`
-}
-
 func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
-	var req CompletionRequest
-	req.Options = Options(api.DefaultOptions())
+	var req llm.CompletionRequest
 	if err := json.NewDecoder(r.Body).Decode(&req); err != nil {
 		http.Error(w, "Bad request", http.StatusBadRequest)
 		return
 	}
 
+	if req.Options == nil {
+		opts := api.DefaultOptions()
+		req.Options = &opts
+	}
+
 	// Set the headers to indicate streaming
 	w.Header().Set("Content-Type", "application/json")
 	w.Header().Set("Transfer-Encoding", "chunked")
@@ -620,26 +572,28 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 		return
 	}
 
-	var samplingParams llama.SamplingParams
-	samplingParams.TopK = req.TopK
-	samplingParams.TopP = req.TopP
-	samplingParams.MinP = req.MinP
-	samplingParams.TypicalP = req.TypicalP
-	samplingParams.Temp = req.Temperature
-	samplingParams.RepeatLastN = req.RepeatLastN
-	samplingParams.PenaltyRepeat = req.RepeatPenalty
-	samplingParams.PenaltyFreq = req.FrequencyPenalty
-	samplingParams.PenaltyPresent = req.PresencePenalty
-	samplingParams.Mirostat = req.Mirostat
-	samplingParams.MirostatTau = req.MirostatTau
-	samplingParams.MirostatEta = req.MirostatEta
-	samplingParams.Seed = uint32(req.Seed)
-	samplingParams.Grammar = req.Grammar
+	// Extract options from the CompletionRequest
+	samplingParams := llama.SamplingParams{
+		TopK:           req.Options.TopK,
+		TopP:           req.Options.TopP,
+		MinP:           req.Options.MinP,
+		TypicalP:       req.Options.TypicalP,
+		Temp:           req.Options.Temperature,
+		RepeatLastN:    req.Options.RepeatLastN,
+		PenaltyRepeat:  req.Options.RepeatPenalty,
+		PenaltyFreq:    req.Options.FrequencyPenalty,
+		PenaltyPresent: req.Options.PresencePenalty,
+		Mirostat:       req.Options.Mirostat,
+		MirostatTau:    req.Options.MirostatTau,
+		MirostatEta:    req.Options.MirostatEta,
+		Seed:           uint32(req.Options.Seed),
+		Grammar:        req.Grammar,
+	}
 
 	seq, err := s.NewSequence(req.Prompt, req.Images, NewSequenceParams{
-		numPredict:     req.NumPredict,
-		stop:           req.Stop,
-		numKeep:        req.NumKeep,
+		numPredict:     req.Options.NumPredict,
+		stop:           req.Options.Stop,
+		numKeep:        req.Options.NumKeep,
 		samplingParams: &samplingParams,
 		embedding:      false,
 	})
@@ -653,7 +607,7 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 		if errors.Is(err, context.Canceled) {
 			slog.Info("aborting completion request due to client closing the connection")
 		} else {
-			slog.Error("Failed to acquire semaphore", "error", err)
+			http.Error(w, fmt.Sprintf("Failed to acquire semaphore: %v", err), http.StatusInternalServerError)
 		}
 		return
 	}
@@ -662,9 +616,10 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 	found := false
 	for i, sq := range s.seqs {
 		if sq == nil {
-			seq.cache, seq.inputs, err = s.cache.LoadCacheSlot(seq.inputs, req.CachePrompt)
+			seq.cache, seq.inputs, err = s.cache.LoadCacheSlot(seq.inputs, true)
 			if err != nil {
 				s.mu.Unlock()
+				s.seqsSem.Release(1)
 				http.Error(w, fmt.Sprintf("Failed to load cache: %v", err), http.StatusInternalServerError)
 				return
 			}
@@ -680,6 +635,7 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 	s.mu.Unlock()
 
 	if !found {
+		s.seqsSem.Release(1)
 		http.Error(w, "could not find an available sequence", http.StatusInternalServerError)
 		return
 	}
@@ -691,7 +647,7 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 			return
 		case content, ok := <-seq.responses:
 			if ok {
-				if err := json.NewEncoder(w).Encode(&CompletionResponse{
+				if err := json.NewEncoder(w).Encode(&llm.CompletionResponse{
 					Content: content,
 				}); err != nil {
 					http.Error(w, fmt.Sprintf("failed to encode response: %v", err), http.StatusInternalServerError)
@@ -702,15 +658,17 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 				flusher.Flush()
 			} else {
 				// Send the final response
-				if err := json.NewEncoder(w).Encode(&CompletionResponse{
-					Stop:         true,
-					StoppedLimit: seq.doneReason == "limit",
-					Timings: Timings{
-						PromptN:     seq.numPromptInputs,
-						PromptMS:    float64(seq.startGenerationTime.Sub(seq.startProcessingTime).Milliseconds()),
-						PredictedN:  seq.numDecoded,
-						PredictedMS: float64(time.Since(seq.startGenerationTime).Milliseconds()),
-					},
+				doneReason := "stop"
+				if seq.doneReason == "limit" {
+					doneReason = "length"
+				}
+				if err := json.NewEncoder(w).Encode(&llm.CompletionResponse{
+					Done:               true,
+					DoneReason:         doneReason,
+					PromptEvalCount:    seq.numPromptInputs,
+					PromptEvalDuration: seq.startGenerationTime.Sub(seq.startProcessingTime),
+					EvalCount:          seq.numDecoded,
+					EvalDuration:       time.Since(seq.startGenerationTime),
 				}); err != nil {
 					http.Error(w, fmt.Sprintf("failed to encode final response: %v", err), http.StatusInternalServerError)
 				}
@@ -721,17 +679,8 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 	}
 }
 
-type EmbeddingRequest struct {
-	Content     string `json:"content"`
-	CachePrompt bool   `json:"cache_prompt"`
-}
-
-type EmbeddingResponse struct {
-	Embedding []float32 `json:"embedding"`
-}
-
 func (s *Server) embeddings(w http.ResponseWriter, r *http.Request) {
-	var req EmbeddingRequest
+	var req llm.EmbeddingRequest
 	if err := json.NewDecoder(r.Body).Decode(&req); err != nil {
 		http.Error(w, fmt.Sprintf("bad request: %s", err), http.StatusBadRequest)
 		return
@@ -752,7 +701,7 @@ func (s *Server) embeddings(w http.ResponseWriter, r *http.Request) {
 		if errors.Is(err, context.Canceled) {
 			slog.Info("aborting embeddings request due to client closing the connection")
 		} else {
-			slog.Error("Failed to acquire semaphore", "error", err)
+			http.Error(w, fmt.Sprintf("Failed to acquire semaphore: %v", err), http.StatusInternalServerError)
 		}
 		return
 	}
@@ -761,9 +710,10 @@ func (s *Server) embeddings(w http.ResponseWriter, r *http.Request) {
 	found := false
 	for i, sq := range s.seqs {
 		if sq == nil {
-			seq.cache, seq.inputs, err = s.cache.LoadCacheSlot(seq.inputs, req.CachePrompt)
+			seq.cache, seq.inputs, err = s.cache.LoadCacheSlot(seq.inputs, false)
 			if err != nil {
 				s.mu.Unlock()
+				s.seqsSem.Release(1)
 				http.Error(w, fmt.Sprintf("Failed to load cache: %v", err), http.StatusInternalServerError)
 				return
 			}
@@ -776,47 +726,24 @@ func (s *Server) embeddings(w http.ResponseWriter, r *http.Request) {
 	s.mu.Unlock()
 
 	if !found {
+		s.seqsSem.Release(1)
 		http.Error(w, "could not find an available sequence", http.StatusInternalServerError)
 		return
 	}
 
 	embedding := <-seq.embedding
 
-	if err := json.NewEncoder(w).Encode(&EmbeddingResponse{
+	if err := json.NewEncoder(w).Encode(&llm.EmbeddingResponse{
 		Embedding: embedding,
 	}); err != nil {
 		http.Error(w, fmt.Sprintf("failed to encode response: %v", err), http.StatusInternalServerError)
 	}
 }
 
-type HealthResponse struct {
-	Status   string  `json:"status"`
-	Progress float32 `json:"progress"`
-}
-
-type ServerStatus int
-
-const (
-	ServerStatusReady ServerStatus = iota
-	ServerStatusLoadingModel
-	ServerStatusError
-)
-
-func (s ServerStatus) ToString() string {
-	switch s {
-	case ServerStatusReady:
-		return "ok"
-	case ServerStatusLoadingModel:
-		return "loading model"
-	default:
-		return "server error"
-	}
-}
-
 func (s *Server) health(w http.ResponseWriter, r *http.Request) {
 	w.Header().Set("Content-Type", "application/json")
-	if err := json.NewEncoder(w).Encode(&HealthResponse{
-		Status:   s.status.ToString(),
+	if err := json.NewEncoder(w).Encode(&llm.ServerStatusResponse{
+		Status:   s.status,
 		Progress: s.progress,
 	}); err != nil {
 		http.Error(w, fmt.Sprintf("failed to encode response: %v", err), http.StatusInternalServerError)
@@ -879,7 +806,7 @@ func (s *Server) loadModel(
 		panic(err)
 	}
 
-	s.status = ServerStatusReady
+	s.status = llm.ServerStatusReady
 	s.ready.Done()
 }
 
@@ -937,7 +864,7 @@ func Execute(args []string) error {
 		parallel:  *parallel,
 		seqs:      make([]*Sequence, *parallel),
 		seqsSem:   semaphore.NewWeighted(int64(*parallel)),
-		status:    ServerStatusLoadingModel,
+		status:    llm.ServerStatusLoadingModel,
 	}
 
 	var tensorSplitFloats []float32

runner/ollamarunner/cache.go

@@ -31,8 +31,10 @@ type InputCache struct {
 	cache kvcache.Cache
 }
 
-func NewInputCache(model model.Model, kvCacheType string, kvSize int32, numSlots int, multiUserCache bool) (*InputCache, error) {
-	if kvSize/int32(numSlots) < 1 {
+func NewInputCache(model model.Model, kvCacheType string, kvSize int32, numSlots int, batchSize int, multiUserCache bool) (*InputCache, error) {
+	numCtx := kvSize / int32(numSlots)
+
+	if numCtx < 1 {
 		return nil, fmt.Errorf("must have at least one kv cache entry per parallel sequence (kv: %v parallel: %v)", kvSize, numSlots)
 	}
 
@@ -44,11 +46,11 @@ func NewInputCache(model model.Model, kvCacheType string, kvSize int32, numSlots
 
 	cache := model.Config().Cache
 	if cache != nil {
-		cache.Init(model.Backend(), kvCacheTypeFromStr(kvCacheType), kvSize)
+		cache.Init(model.Backend(), kvCacheTypeFromStr(kvCacheType), numSlots, int(numCtx), batchSize)
 	}
 
 	return &InputCache{
-		numCtx:         kvSize / int32(numSlots),
+		numCtx:         numCtx,
 		enabled:        cache != nil,
 		slots:          slots,
 		multiUserCache: multiUserCache,
@@ -89,7 +91,7 @@ type InputCacheSlot struct {
 	lastUsed time.Time
 }
 
-func (c *InputCache) LoadCacheSlot(prompt []input.Input, cachePrompt bool) (*InputCacheSlot, []input.Input, error) {
+func (c *InputCache) LoadCacheSlot(prompt []input.Input) (*InputCacheSlot, []input.Input, error) {
 	var slot *InputCacheSlot
 	var numPast int32
 	var err error
@@ -107,10 +109,6 @@ func (c *InputCache) LoadCacheSlot(prompt []input.Input, cachePrompt bool) (*Inp
 		return nil, nil, err
 	}
 
-	if !cachePrompt {
-		numPast = 0
-	}
-
 	slot.InUse = true
 	slot.lastUsed = time.Now()
 
@@ -120,6 +118,10 @@ func (c *InputCache) LoadCacheSlot(prompt []input.Input, cachePrompt bool) (*Inp
 	}
 
 	if c.cache != nil {
+		if numPast > 0 && !c.cache.CanResume(slot.Id, numPast) {
+			numPast = 0
+		}
+
 		err = c.cache.Remove(slot.Id, numPast, math.MaxInt32)
 		if err != nil {
 			// Some models don't support partial erasure
@@ -227,6 +229,8 @@ func countCommonPrefix(a []input.Input, b []input.Input) int32 {
 	return count
 }
 
+// TODO(jessegross): If we need to reprocess the inputs we should ensure that
+// we don't split up a SameBatch
 func (c *InputCache) ShiftDiscard(inputLen int32, numKeep int32) int32 {
 	targetFree := (c.numCtx - numKeep) / 2
 	targetFree = max(targetFree, 1)
@@ -241,6 +245,14 @@ func (c *InputCache) ShiftDiscard(inputLen int32, numKeep int32) int32 {
 	return discard
 }
 
+type ErrReprocessInputs struct {
+	Inputs []input.Input
+}
+
+func (e *ErrReprocessInputs) Error() string {
+	return fmt.Sprintf("kv cache shift not supported, inputs need reprocessing (input count: %v)", len(e.Inputs))
+}
+
 // Frees up space in the KV cache by deleting the oldest half of history and shifting
 // the newest half into that space (saving numKeep inputs at the beginning).
 //
@@ -260,11 +272,23 @@ func (c *InputCache) ShiftCacheSlot(slot *InputCacheSlot, numKeep int32) error {
 	slog.Debug("context limit hit - shifting", "id", slot.Id, "limit", c.numCtx, "input", len(slot.Inputs),
 		"keep", numKeep, "discard", discard)
 
-	// TODO (jessegross): KV cache removal can fail for certain types of models
 	if c.cache != nil {
 		err := c.cache.Remove(slot.Id, numKeep, numKeep+discard)
 		if err != nil {
-			return fmt.Errorf("unable to remove old kv cache entries (id: %v, keep: %v discard: %v): %w", slot.Id, numKeep, discard, err)
+			slog.Debug("kv cache removal unsupported, clearing cache and returning inputs for reprocessing",
+				"id", slot.Id, "error", err)
+
+			// Create new input slice with preserved tokens (numKeep + remaining tokens after discard)
+			newInputs := make([]input.Input, numKeep+inputLen-(numKeep+discard))
+			copy(newInputs[:numKeep], slot.Inputs[:numKeep])
+			copy(newInputs[numKeep:], slot.Inputs[numKeep+discard:])
+
+			// Reset the cache
+			_ = c.cache.Remove(slot.Id, 0, -1)
+			slot.Inputs = []input.Input{}
+
+			// Return error with inputs that need to be reprocessed
+			return &ErrReprocessInputs{Inputs: newInputs}
 		}
 	}
 

runner/ollamarunner/cache_test.go

@@ -1,10 +1,13 @@
 package ollamarunner
 
 import (
+	"errors"
+	"fmt"
 	"image"
 	"testing"
 	"time"
 
+	"github.com/ollama/ollama/ml"
 	"github.com/ollama/ollama/model/input"
 )
 
@@ -297,3 +300,220 @@ func TestShiftDiscard(t *testing.T) {
 		})
 	}
 }
+
+func TestLoadCacheSlot(t *testing.T) {
+	tests := []struct {
+		name           string
+		cache          InputCache
+		prompt         []input.Input
+		wantErr        bool
+		expectedSlotId int
+		expectedPrompt int // expected length of remaining prompt
+	}{
+		{
+			name: "Basic cache hit - single user",
+			cache: InputCache{
+				multiUserCache: false,
+				slots: []InputCacheSlot{
+					{
+						Id:       0,
+						Inputs:   []input.Input{{Token: 1}, {Token: 2}},
+						InUse:    false,
+						lastUsed: time.Now().Add(-time.Second),
+					},
+					{
+						Id:       1,
+						Inputs:   []input.Input{},
+						InUse:    false,
+						lastUsed: time.Now().Add(-2 * time.Second),
+					},
+				},
+			},
+			prompt:         []input.Input{{Token: 1}, {Token: 2}, {Token: 3}},
+			wantErr:        false,
+			expectedSlotId: 0,
+			expectedPrompt: 1, // Only token 3 remains
+		},
+		{
+			name: "Basic cache hit - multi user",
+			cache: InputCache{
+				multiUserCache: true,
+				slots: []InputCacheSlot{
+					{
+						Id:       0,
+						Inputs:   []input.Input{{Token: 1}, {Token: 2}},
+						InUse:    false,
+						lastUsed: time.Now().Add(-time.Second),
+					},
+					{
+						Id:       1,
+						Inputs:   []input.Input{},
+						InUse:    false,
+						lastUsed: time.Now().Add(-2 * time.Second),
+					},
+				},
+			},
+			prompt:         []input.Input{{Token: 1}, {Token: 2}, {Token: 3}},
+			wantErr:        false,
+			expectedSlotId: 0,
+			expectedPrompt: 1, // Only token 3 remains
+		},
+		{
+			name: "Exact match - leave one input",
+			cache: InputCache{
+				multiUserCache: false,
+				slots: []InputCacheSlot{
+					{
+						Id:       0,
+						Inputs:   []input.Input{{Token: 1}, {Token: 2}},
+						InUse:    false,
+						lastUsed: time.Now().Add(-time.Second),
+					},
+				},
+			},
+			prompt:         []input.Input{{Token: 1}, {Token: 2}},
+			wantErr:        false,
+			expectedSlotId: 0,
+			expectedPrompt: 1, // Should leave 1 token for sampling
+		},
+		{
+			name: "No available slots",
+			cache: InputCache{
+				multiUserCache: false,
+				slots: []InputCacheSlot{
+					{
+						Id:       0,
+						Inputs:   []input.Input{{Token: 1}, {Token: 2}},
+						InUse:    true,
+						lastUsed: time.Now().Add(-time.Second),
+					},
+				},
+			},
+			prompt:         []input.Input{{Token: 1}, {Token: 2}, {Token: 3}},
+			wantErr:        true,
+			expectedSlotId: -1,
+			expectedPrompt: -1,
+		},
+	}
+
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			slot, remainingPrompt, err := tt.cache.LoadCacheSlot(tt.prompt)
+
+			// Check error state
+			if (err != nil) != tt.wantErr {
+				t.Errorf("LoadCacheSlot() error = %v, wantErr %v", err, tt.wantErr)
+				return
+			}
+
+			if tt.wantErr {
+				return // Skip further checks if we expected an error
+			}
+
+			// Verify slot ID
+			if slot.Id != tt.expectedSlotId {
+				t.Errorf("LoadCacheSlot() slot ID = %v, expected %v", slot.Id, tt.expectedSlotId)
+			}
+
+			// Verify slot is now marked in use
+			if !slot.InUse {
+				t.Errorf("LoadCacheSlot() slot not marked InUse")
+			}
+
+			// Verify remaining prompt length
+			if len(remainingPrompt) != tt.expectedPrompt {
+				t.Errorf("LoadCacheSlot() remaining prompt length = %v, expected %v",
+					len(remainingPrompt), tt.expectedPrompt)
+			}
+		})
+	}
+}
+
+// Mock implementation of the Cache interface
+type mockCache struct {
+	shouldFail bool
+}
+
+// Implement only the methods needed for the test
+func (m *mockCache) Remove(seq int, beginIndex, endIndex int32) error {
+	if m.shouldFail {
+		return fmt.Errorf("mock cache removal error")
+	}
+	return nil
+}
+
+// Stub implementations for other interface methods
+func (m *mockCache) SetLayer(layer int)                                                            {}
+func (m *mockCache) Get(ctx ml.Context) (ml.Tensor, ml.Tensor, ml.Tensor)                          { return nil, nil, nil }
+func (m *mockCache) Put(ctx ml.Context, key, value ml.Tensor)                                      {}
+func (m *mockCache) Init(backend ml.Backend, dtype ml.DType, maxSequences, capacity, maxBatch int) {}
+func (m *mockCache) Close()                                                                        {}
+func (m *mockCache) StartForward(ctx ml.Context, batch input.Batch) error                          { return nil }
+func (m *mockCache) CopyPrefix(srcSeq, dstSeq int, len int32)                                      {}
+func (m *mockCache) SetConfig(ml.CacheConfig)                                                      {}
+func (m *mockCache) CanResume(seq int, pos int32) bool                                             { return true }
+
+func TestShiftCacheSlot(t *testing.T) {
+	tests := []struct {
+		name          string
+		numCtx        int32
+		inputs        []input.Input
+		numKeep       int32
+		cacheErr      bool
+		wantErr       any
+		wantInputsLen int
+	}{
+		{
+			name:          "Normal shift",
+			numCtx:        10,
+			inputs:        []input.Input{{Token: 1}, {Token: 2}, {Token: 3}, {Token: 4}, {Token: 5}, {Token: 6}, {Token: 7}, {Token: 8}, {Token: 9}, {Token: 10}},
+			numKeep:       2,
+			cacheErr:      false, // No error
+			wantErr:       nil,
+			wantInputsLen: 6, // After discarding 4 tokens
+		},
+		{
+			name:          "Cache removal fails",
+			numCtx:        10,
+			inputs:        []input.Input{{Token: 1}, {Token: 2}, {Token: 3}, {Token: 4}, {Token: 5}, {Token: 6}, {Token: 7}, {Token: 8}, {Token: 9}, {Token: 10}},
+			numKeep:       2,
+			cacheErr:      true,
+			wantErr:       &ErrReprocessInputs{},
+			wantInputsLen: 0, // Original inputs should be cleared
+		},
+	}
+
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			mock := &mockCache{shouldFail: tt.cacheErr}
+			c := InputCache{
+				numCtx: tt.numCtx,
+				cache:  mock,
+			}
+			slot := &InputCacheSlot{
+				Id:     123,
+				Inputs: make([]input.Input, len(tt.inputs)),
+			}
+			copy(slot.Inputs, tt.inputs)
+
+			err := c.ShiftCacheSlot(slot, tt.numKeep)
+
+			if tt.wantErr != nil {
+				if err == nil {
+					t.Errorf("Expected error but got nil")
+					return
+				}
+
+				if !errors.As(err, &tt.wantErr) {
+					t.Errorf("Expected error of type %T but got %T: %v", tt.wantErr, err, err)
+				}
+			} else if err != nil {
+				t.Errorf("Unexpected error: %v", err)
+			}
+
+			if len(slot.Inputs) != tt.wantInputsLen {
+				t.Errorf("Slot inputs length after operation: got %v, want %v", len(slot.Inputs), tt.wantInputsLen)
+			}
+		})
+	}
+}

runner/ollamarunner/runner.go

@@ -24,6 +24,7 @@ import (
 	"golang.org/x/sync/semaphore"
 
 	"github.com/ollama/ollama/api"
+	"github.com/ollama/ollama/llm"
 	"github.com/ollama/ollama/ml"
 	"github.com/ollama/ollama/model"
 	"github.com/ollama/ollama/model/input"
@@ -33,10 +34,14 @@ import (
 	_ "github.com/ollama/ollama/model/models"
 )
 
+type contextList struct {
+	list []ml.Context
+}
+
 type Sequence struct {
-	// ctx for allocating tensors that last the lifetime of the sequence, such as
+	// ctxs are used for allocating tensors that last the lifetime of the sequence, such as
 	// multimodal embeddings
-	ctx ml.Context
+	ctxs *contextList
 
 	// batch index
 	iBatch int
@@ -94,13 +99,12 @@ type NewSequenceParams struct {
 	embedding  bool
 }
 
-func (s *Server) NewSequence(prompt string, images []ImageData, params NewSequenceParams) (*Sequence, error) {
+func (s *Server) NewSequence(prompt string, images []llm.ImageData, params NewSequenceParams) (*Sequence, error) {
 	s.ready.Wait()
 
 	startTime := time.Now()
-	ctx := s.model.Backend().NewContext()
 
-	inputs, err := s.inputs(ctx, prompt, images)
+	inputs, ctxs, err := s.inputs(prompt, images)
 	if err != nil {
 		return nil, fmt.Errorf("failed to process inputs: %w", err)
 	} else if len(inputs) == 0 {
@@ -116,8 +120,36 @@ func (s *Server) NewSequence(prompt string, images []ImageData, params NewSequen
 
 	if int32(len(inputs)) > s.cache.numCtx {
 		discard := int32(len(inputs)) - s.cache.numCtx
+		promptStart := params.numKeep + discard
+
+		// If we need to truncate in the middle of a unbreakable batch, remove the entire batch
+		sameBatch := 0
+		for i, inp := range inputs {
+			if sameBatch > 0 {
+				sameBatch--
+
+				if promptStart == int32(i) {
+					promptStart++
+				}
+			} else if promptStart == int32(i) {
+				break
+			}
+
+			if inp.SameBatch != 0 {
+				if int32(i) < params.numKeep {
+					return nil, fmt.Errorf("SameBatch may not be specified within numKeep (index: %v numKeep: %v SameBatch: %v)", i, params.numKeep, inp.SameBatch)
+				}
+
+				sameBatch = inp.SameBatch
+			}
+		}
+
+		if promptStart >= int32(len(inputs)) {
+			return nil, errors.New("entire prompt removed by truncation")
+		}
+
 		newInputs := inputs[:params.numKeep]
-		newInputs = append(newInputs, inputs[params.numKeep+discard:]...)
+		newInputs = append(newInputs, inputs[promptStart:]...)
 
 		slog.Warn("truncating input prompt", "limit", s.cache.numCtx, "prompt", len(inputs), "keep", params.numKeep, "new", len(newInputs))
 		inputs = newInputs
@@ -126,7 +158,7 @@ func (s *Server) NewSequence(prompt string, images []ImageData, params NewSequen
 	// TODO(jessegross): Ingest cached history for grammar
 
 	return &Sequence{
-		ctx:                 ctx,
+		ctxs:                ctxs,
 		inputs:              inputs,
 		numPromptInputs:     len(inputs),
 		startProcessingTime: startTime,
@@ -145,7 +177,7 @@ func (s *Server) NewSequence(prompt string, images []ImageData, params NewSequen
 // inputs processes the prompt and images into a list of inputs
 // by splitting the prompt on [img-<n>] tags, tokenizing text and
 // decoding images
-func (s *Server) inputs(ctx ml.Context, prompt string, images []ImageData) ([]input.Input, error) {
+func (s *Server) inputs(prompt string, images []llm.ImageData) ([]input.Input, *contextList, error) {
 	var inputs []input.Input
 	var parts []string
 	var matches [][]string
@@ -160,12 +192,19 @@ func (s *Server) inputs(ctx ml.Context, prompt string, images []ImageData) ([]in
 		parts = []string{prompt}
 	}
 
+	var contexts contextList
+	runtime.AddCleanup(&contexts, func(ctxs []ml.Context) {
+		for _, ctx := range ctxs {
+			ctx.Close()
+		}
+	}, contexts.list)
+
 	postTokenize := false
 	for i, part := range parts {
 		// text - tokenize
 		tokens, err := s.model.(model.TextProcessor).Encode(part, i == 0)
 		if err != nil {
-			return nil, err
+			return nil, nil, err
 		}
 
 		for _, t := range tokens {
@@ -185,12 +224,14 @@ func (s *Server) inputs(ctx ml.Context, prompt string, images []ImageData) ([]in
 			}
 
 			if imageIndex < 0 {
-				return nil, fmt.Errorf("invalid image index: %d", n)
+				return nil, nil, fmt.Errorf("invalid image index: %d", n)
 			}
 
+			ctx := s.model.Backend().NewContext()
+			contexts.list = append(contexts.list, ctx)
 			imageEmbeddings, err := multimodalProcessor.EncodeMultimodal(ctx, images[imageIndex].Data)
 			if err != nil {
-				return nil, err
+				return nil, nil, err
 			}
 
 			s.multimodalHash.Reset()
@@ -204,13 +245,13 @@ func (s *Server) inputs(ctx ml.Context, prompt string, images []ImageData) ([]in
 
 	if visionModel && postTokenize {
 		var err error
-		inputs, err = multimodalProcessor.PostTokenize(ctx, inputs)
+		inputs, err = multimodalProcessor.PostTokenize(inputs)
 		if err != nil {
-			return nil, err
+			return nil, nil, err
 		}
 	}
 
-	return inputs, nil
+	return inputs, &contexts, nil
 }
 
 type Server struct {
@@ -222,7 +263,7 @@ type Server struct {
 	model model.Model
 
 	// status for external health reporting - loading, ready to serve, etc.
-	status ServerStatus
+	status llm.ServerStatus
 
 	// current progress on loading the model
 	progress float32
@@ -251,6 +292,9 @@ type Server struct {
 	// KV cache
 	cache *InputCache
 
+	// next sequence for prompt processing to avoid starvation
+	nextSeq int
+
 	// multimodalHash generates hashes for comparing equality
 	// of non-text data
 	multimodalHash maphash.Hash
@@ -305,7 +349,6 @@ func (s *Server) removeSequence(seqIndex int, reason string) {
 	close(seq.responses)
 	close(seq.embedding)
 	seq.cache.InUse = false
-	seq.ctx.Close()
 	s.seqs[seqIndex] = nil
 	s.seqsSem.Release(1)
 }
@@ -333,16 +376,22 @@ func (s *Server) processBatch() error {
 	}
 	defer s.mu.Unlock()
 
-	var options input.Options
+	var batchInputs []int32
+	var batch input.Batch
+
+	resumeSeq := -1
+	seqIdx := s.nextSeq - 1
+	for range s.seqs {
+		seqIdx = (seqIdx + 1) % len(s.seqs)
+		seq := s.seqs[seqIdx]
 
-	for i, seq := range s.seqs {
 		if seq == nil {
 			continue
 		}
 
 		// if past the num predict limit
 		if seq.numPredict > 0 && seq.numPredicted >= seq.numPredict {
-			s.removeSequence(i, "limit")
+			s.removeSequence(seqIdx, "limit")
 			continue
 		}
 
@@ -351,33 +400,61 @@ func (s *Server) processBatch() error {
 			seq.cache.Inputs = []input.Input{}
 		}
 
-		for j, inp := range seq.inputs {
-			if int32(len(seq.cache.Inputs)+len(seq.pendingInputs)+1) > s.cache.numCtx {
-				if len(seq.pendingInputs) == 0 {
-					err := s.cache.ShiftCacheSlot(seq.cache, seq.numKeep)
-					if err != nil {
-						return err
-					}
-				} else {
-					break
-				}
+		batchSize := s.batchSize
+
+		for i, inp := range seq.inputs {
+			// If we are required to put following inputs into a single batch then extend the
+			// batch size. Since we are only extending the size the minimum amount possible, this
+			// will cause a break if we have existing inputs.
+			minBatch := 1 + inp.SameBatch
+			if minBatch > batchSize {
+				batchSize = minBatch
 			}
 
-			if j >= s.batchSize {
+			// Stop if the required batch would put us over the total batch size (including tokens
+			// added by other sequences). If we haven't been able to add anything yet then pick up
+			// here again for the next batch to avoid starvation, though we can opportunistically
+			// check if other sequences can still squeeze something in.
+			if len(batchInputs)+minBatch > batchSize {
+				if len(seq.pendingInputs) == 0 && resumeSeq == -1 {
+					resumeSeq = seqIdx
+				}
 				break
 			}
 
-			options.Inputs = append(options.Inputs, inp.Token)
-			if inp.Multimodal != nil {
-				options.Multimodal = append(options.Multimodal, input.MultimodalIndex{Index: len(options.Inputs) - 1, Multimodal: inp.Multimodal})
+			// If the sum of our working set (already processed tokens, tokens we added to this
+			// batch, required following tokens) exceeds the context size, then trigger a shift
+			// now so we don't have to do one later when we can't break the batch.
+			if int32(len(seq.cache.Inputs)+len(seq.pendingInputs)+minBatch) > s.cache.numCtx {
+				if len(seq.pendingInputs) != 0 {
+					break
+				}
+
+				err := s.cache.ShiftCacheSlot(seq.cache, seq.numKeep)
+				if err != nil {
+					var reprocess *ErrReprocessInputs
+					if errors.As(err, &reprocess) {
+						// Prepend these inputs to the sequence's inputs queue for reprocessing
+						seq.inputs = append(reprocess.Inputs, seq.inputs...)
+						// Skip this sequence but continue processing the rest
+						continue
+					} else {
+						return err
+					}
+				}
 			}
 
-			options.Positions = append(options.Positions, int32(len(seq.cache.Inputs)+len(seq.pendingInputs)))
-			options.Sequences = append(options.Sequences, seq.cache.Id)
+			batchInputs = append(batchInputs, inp.Token)
+			if inp.Multimodal != nil {
+				batch.Multimodal = append(batch.Multimodal, input.MultimodalIndex{Index: len(batchInputs) - 1, Multimodal: inp.Multimodal})
+			}
 
-			seq.iBatch = len(options.Outputs)
-			if j+1 == len(seq.inputs) {
-				options.Outputs = append(options.Outputs, int32(len(options.Inputs)-1))
+			batch.Positions = append(batch.Positions, int32(len(seq.cache.Inputs)+len(seq.pendingInputs)))
+			batch.Sequences = append(batch.Sequences, seq.cache.Id)
+
+			seq.iBatch = len(batch.Outputs)
+			if i+1 == len(seq.inputs) {
+				batch.Outputs = append(batch.Outputs, int32(len(batchInputs)-1))
 			}
 			seq.pendingInputs = append(seq.pendingInputs, inp)
 		}
@@ -385,14 +462,20 @@ func (s *Server) processBatch() error {
 		seq.inputs = seq.inputs[len(seq.pendingInputs):]
 	}
 
-	if len(options.Inputs) == 0 {
+	if resumeSeq != -1 {
+		s.nextSeq = resumeSeq
+	} else {
+		s.nextSeq = seqIdx + 1
+	}
+
+	if len(batchInputs) == 0 {
 		return nil
 	}
 
 	ctx := s.model.Backend().NewContext()
 	defer ctx.Close()
 
-	modelOutput, err := model.Forward(ctx, s.model, options)
+	modelOutput, err := model.Forward(ctx, s.model, batchInputs, batch)
 	if err != nil {
 		return fmt.Errorf("failed to decode batch: %w", err)
 	}
@@ -432,7 +515,7 @@ func (s *Server) processBatch() error {
 		}
 
 		// sample a token
-		vocabSize := len(logits) / len(options.Outputs)
+		vocabSize := len(logits) / len(batch.Outputs)
 
 		token, err := seq.sampler.Sample(logits[seq.iBatch*vocabSize : (seq.iBatch+1)*vocabSize])
 		if err != nil {
@@ -501,75 +584,18 @@ func (s *Server) processBatch() error {
 	return nil
 }
 
-// TODO (jmorganca): use structs from the api package to avoid duplication
-// this way the api acts as a proxy instead of using a different api for the
-// runner
-type Options struct {
-	api.Runner
-
-	NumKeep          int      `json:"n_keep"`
-	Seed             int      `json:"seed"`
-	NumPredict       int      `json:"n_predict"`
-	TopK             int      `json:"top_k"`
-	TopP             float32  `json:"top_p"`
-	MinP             float32  `json:"min_p"`
-	TypicalP         float32  `json:"typical_p"`
-	RepeatLastN      int      `json:"repeat_last_n"`
-	Temperature      float32  `json:"temperature"`
-	RepeatPenalty    float32  `json:"repeat_penalty"`
-	PresencePenalty  float32  `json:"presence_penalty"`
-	FrequencyPenalty float32  `json:"frequency_penalty"`
-	Mirostat         int      `json:"mirostat"`
-	MirostatTau      float32  `json:"mirostat_tau"`
-	MirostatEta      float32  `json:"mirostat_eta"`
-	Stop             []string `json:"stop"`
-}
-
-type ImageData struct {
-	Data          []byte `json:"data"`
-	ID            int    `json:"id"`
-	AspectRatioID int    `json:"aspect_ratio_id"`
-}
-
-type CompletionRequest struct {
-	Prompt      string      `json:"prompt"`
-	Images      []ImageData `json:"image_data"`
-	Grammar     string      `json:"grammar"`
-	CachePrompt bool        `json:"cache_prompt"`
-
-	Options
-}
-
-type Timings struct {
-	PredictedN  int     `json:"predicted_n"`
-	PredictedMS float64 `json:"predicted_ms"`
-	PromptN     int     `json:"prompt_n"`
-	PromptMS    float64 `json:"prompt_ms"`
-}
-
-type CompletionResponse struct {
-	Content string `json:"content"`
-	Stop    bool   `json:"stop"`
-
-	Model        string  `json:"model,omitempty"`
-	Prompt       string  `json:"prompt,omitempty"`
-	StoppedLimit bool    `json:"stopped_limit,omitempty"`
-	PredictedN   int     `json:"predicted_n,omitempty"`
-	PredictedMS  float64 `json:"predicted_ms,omitempty"`
-	PromptN      int     `json:"prompt_n,omitempty"`
-	PromptMS     float64 `json:"prompt_ms,omitempty"`
-
-	Timings Timings `json:"timings"`
-}
-
 func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
-	var req CompletionRequest
-	req.Options = Options(api.DefaultOptions())
+	var req llm.CompletionRequest
 	if err := json.NewDecoder(r.Body).Decode(&req); err != nil {
 		http.Error(w, "Bad request", http.StatusBadRequest)
 		return
 	}
 
+	if req.Options == nil {
+		opts := api.DefaultOptions()
+		req.Options = &opts
+	}
+
 	// Set the headers to indicate streaming
 	w.Header().Set("Content-Type", "application/json")
 	w.Header().Set("Transfer-Encoding", "chunked")
@@ -591,18 +617,18 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 	}
 
 	sampler := sample.NewSampler(
-		req.Temperature,
-		req.TopK,
-		req.TopP,
-		req.MinP,
-		req.Seed,
+		req.Options.Temperature,
+		req.Options.TopK,
+		req.Options.TopP,
+		req.Options.MinP,
+		req.Options.Seed,
 		grammar,
 	)
 
 	seq, err := s.NewSequence(req.Prompt, req.Images, NewSequenceParams{
-		numPredict: req.NumPredict,
-		stop:       req.Stop,
-		numKeep:    int32(req.NumKeep),
+		numPredict: req.Options.NumPredict,
+		stop:       req.Options.Stop,
+		numKeep:    int32(req.Options.NumKeep),
 		sampler:    sampler,
 		embedding:  false,
 	})
@@ -616,7 +642,7 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 		if errors.Is(err, context.Canceled) {
 			slog.Info("aborting completion request due to client closing the connection")
 		} else {
-			slog.Error("Failed to acquire semaphore", "error", err)
+			http.Error(w, fmt.Sprintf("Failed to acquire semaphore: %v", err), http.StatusInternalServerError)
 		}
 		return
 	}
@@ -625,9 +651,10 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 	found := false
 	for i, sq := range s.seqs {
 		if sq == nil {
-			seq.cache, seq.inputs, err = s.cache.LoadCacheSlot(seq.inputs, req.CachePrompt)
+			seq.cache, seq.inputs, err = s.cache.LoadCacheSlot(seq.inputs)
 			if err != nil {
 				s.mu.Unlock()
+				s.seqsSem.Release(1)
 				http.Error(w, fmt.Sprintf("Failed to load cache: %v", err), http.StatusInternalServerError)
 				return
 			}
@@ -641,6 +668,7 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 	s.mu.Unlock()
 
 	if !found {
+		s.seqsSem.Release(1)
 		http.Error(w, "could not find an available sequence", http.StatusInternalServerError)
 		return
 	}
@@ -652,7 +680,7 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 			return
 		case content, ok := <-seq.responses:
 			if ok {
-				if err := json.NewEncoder(w).Encode(&CompletionResponse{
+				if err := json.NewEncoder(w).Encode(&llm.CompletionResponse{
 					Content: content,
 				}); err != nil {
 					http.Error(w, fmt.Sprintf("failed to encode response: %v", err), http.StatusInternalServerError)
@@ -663,15 +691,17 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 				flusher.Flush()
 			} else {
 				// Send the final response
-				if err := json.NewEncoder(w).Encode(&CompletionResponse{
-					Stop:         true,
-					StoppedLimit: seq.doneReason == "limit",
-					Timings: Timings{
-						PromptN:     seq.numPromptInputs,
-						PromptMS:    float64(seq.startGenerationTime.Sub(seq.startProcessingTime).Milliseconds()),
-						PredictedN:  seq.numPredicted,
-						PredictedMS: float64(time.Since(seq.startGenerationTime).Milliseconds()),
-					},
+				doneReason := "stop"
+				if seq.doneReason == "limit" {
+					doneReason = "length"
+				}
+				if err := json.NewEncoder(w).Encode(&llm.CompletionResponse{
+					Done:               true,
+					DoneReason:         doneReason,
+					PromptEvalCount:    seq.numPromptInputs,
+					PromptEvalDuration: seq.startGenerationTime.Sub(seq.startProcessingTime),
+					EvalCount:          seq.numPredicted,
+					EvalDuration:       time.Since(seq.startGenerationTime),
 				}); err != nil {
 					http.Error(w, fmt.Sprintf("failed to encode final response: %v", err), http.StatusInternalServerError)
 				}
@@ -682,43 +712,10 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 	}
 }
 
-type EmbeddingRequest struct {
-	Content     string `json:"content"`
-	CachePrompt bool   `json:"cache_prompt"`
-}
-
-type EmbeddingResponse struct {
-	Embedding []float32 `json:"embedding"`
-}
-
-type HealthResponse struct {
-	Status   string  `json:"status"`
-	Progress float32 `json:"progress"`
-}
-
-type ServerStatus int
-
-const (
-	ServerStatusReady ServerStatus = iota
-	ServerStatusLoadingModel
-	ServerStatusError
-)
-
-func (s ServerStatus) ToString() string {
-	switch s {
-	case ServerStatusReady:
-		return "ok"
-	case ServerStatusLoadingModel:
-		return "loading model"
-	default:
-		return "server error"
-	}
-}
-
 func (s *Server) health(w http.ResponseWriter, r *http.Request) {
 	w.Header().Set("Content-Type", "application/json")
-	if err := json.NewEncoder(w).Encode(&HealthResponse{
-		Status:   s.status.ToString(),
+	if err := json.NewEncoder(w).Encode(&llm.ServerStatusResponse{
+		Status:   s.status,
 		Progress: s.progress,
 	}); err != nil {
 		http.Error(w, fmt.Sprintf("failed to encode response: %v", err), http.StatusInternalServerError)
@@ -737,6 +734,7 @@ func (m *multiLPath) String() string {
 }
 
 func (s *Server) loadModel(
+	ctx context.Context,
 	mpath string,
 	params ml.BackendParams,
 	lpath multiLPath,
@@ -746,7 +744,7 @@ func (s *Server) loadModel(
 	multiUserCache bool,
 ) {
 	var err error
-	s.model, err = model.New(mpath, params)
+	s.model, err = model.New(ctx, mpath, params)
 	if err != nil {
 		panic(err)
 	}
@@ -758,7 +756,7 @@ func (s *Server) loadModel(
 		panic("loras are not yet implemented")
 	}
 
-	s.cache, err = NewInputCache(s.model, kvCacheType, int32(kvSize), parallel, multiUserCache)
+	s.cache, err = NewInputCache(s.model, kvCacheType, int32(kvSize), parallel, s.batchSize, multiUserCache)
 	if err != nil {
 		panic(err)
 	}
@@ -772,7 +770,7 @@ func (s *Server) loadModel(
 	s.seqs = make([]*Sequence, s.parallel)
 	s.seqsSem = semaphore.NewWeighted(int64(s.parallel))
 
-	s.status = ServerStatusReady
+	s.status = llm.ServerStatusReady
 	s.ready.Done()
 }
 
@@ -824,7 +822,7 @@ func Execute(args []string) error {
 
 	server := &Server{
 		batchSize: *batchSize,
-		status:    ServerStatusLoadingModel,
+		status:    llm.ServerStatusLoadingModel,
 	}
 
 	// TODO(jessegross): Parameters that need to be implemented:
@@ -842,6 +840,9 @@ func Execute(args []string) error {
 	}
 
 	params := ml.BackendParams{
+		Progress: func(progress float32) {
+			server.progress = progress
+		},
 		NumThreads:     *threads,
 		NumGPULayers:   *numGPULayers,
 		MainGPU:        *mainGPU,
@@ -850,13 +851,13 @@ func Execute(args []string) error {
 	}
 
 	server.ready.Add(1)
-	go server.loadModel(*mpath, params, lpaths, *parallel, *kvCacheType, *kvSize, *multiUserCache)
-
-	server.cond = sync.NewCond(&server.mu)
-
 	ctx, cancel := context.WithCancel(context.Background())
 	defer cancel()
 
+	go server.loadModel(ctx, *mpath, params, lpaths, *parallel, *kvCacheType, *kvSize, *multiUserCache)
+
+	server.cond = sync.NewCond(&server.mu)
+
 	go server.run(ctx)
 
 	addr := "127.0.0.1:" + strconv.Itoa(*port)

sample/samplers.go

@@ -26,6 +26,10 @@ type Sampler struct {
 }
 
 func (s *Sampler) Sample(logits []float32) (int32, error) {
+	if len(logits) == 0 {
+		return -1, errors.New("sample: no logits provided to sample")
+	}
+
 	tokens := make([]token, len(logits))
 	for i := range logits {
 		tokens[i].id = int32(i)
@@ -87,19 +91,13 @@ func (s *Sampler) sample(tokens []token) (token, error) {
 	// topK also sorts the tokens in descending order of logits
 	tokens = topK(tokens, s.topK)
 
-	tokens = temperature(tokens, s.temperature)
-	tokens = softmax(tokens)
+	// scale and normalize the tokens in place
+	temperature(tokens, s.temperature)
+	softmax(tokens)
 
 	tokens = topP(tokens, s.topP)
 	tokens = minP(tokens, s.minP)
 
-	// TODO: this should fall back to greedy sampling
-	// or topP, topK values etc should be such that
-	// there are always tokens to sample from
-	if len(tokens) == 0 {
-		return token{}, errors.New("no tokens to sample from")
-	}
-
 	var r float32
 	if s.rng != nil {
 		r = s.rng.Float32()
@@ -122,6 +120,9 @@ func (s *Sampler) sample(tokens []token) (token, error) {
 		return 1
 	})
 
+	if math.IsNaN(float64(sum)) {
+		return token{}, errors.New("sample: logits sum to NaN, check model output")
+	}
 	return tokens[idx], nil
 }
 

sample/samplers_test.go

@@ -1,6 +1,7 @@
 package sample
 
 import (
+	"math"
 	"math/rand/v2"
 	"testing"
 )
@@ -29,6 +30,29 @@ func TestWeighted(t *testing.T) {
 	if want != got {
 		t.Errorf("index mismatch: want %d, got %d", want, got)
 	}
+
+	// Test very high p
+	logits = []float32{1.0, 0.9999999999999999, 0.5, 0.1}
+	// Use extremely small topP to filter out all tokens
+	sampler = NewSampler(1.0, 0, 1e-10, 0, 0, nil)
+	got, err = sampler.Sample(logits)
+	if err != nil {
+		t.Error(err)
+		return
+	}
+	// Should get the token with the highest logit
+	want = int32(0)
+	if want != got {
+		t.Errorf("index mismatch: want %d, got %d", want, got)
+	}
+
+	logits = []float32{float32(math.NaN()), float32(math.NaN()), float32(math.NaN())}
+	sampler = NewSampler(1, 0, 0.95, 0.05, 0, nil)
+	got, err = sampler.Sample(logits)
+	if err == nil {
+		t.Errorf("expected error, got %d", got)
+		return
+	}
 }
 
 func BenchmarkSample(b *testing.B) {

sample/transforms.go

@@ -26,17 +26,16 @@ func (h *tokenHeap) Pop() any {
 }
 
 // temperature applies scaling to the logits
-func temperature(ts []token, temp float32) []token {
+func temperature(ts []token, temp float32) {
 	// Ensure temperature clipping near 0 to avoid numerical instability
 	temp = max(temp, 1e-7)
 	for i := range ts {
 		ts[i].value = ts[i].value / temp
 	}
-	return ts
 }
 
 // softmax applies normalization to the logits
-func softmax(ts []token) []token {
+func softmax(ts []token) {
 	// Find max logit for numerical stability
 	maxLogit := float32(math.Inf(-1))
 	for _, t := range ts {
@@ -56,8 +55,6 @@ func softmax(ts []token) []token {
 	for i := range ts {
 		ts[i].value /= sum
 	}
-
-	return ts
 }
 
 // topK limits the number of tokens considered to the k highest logits
@@ -99,6 +96,7 @@ func topK(ts []token, k int) []token {
 }
 
 // topP limits tokens to those with cumulative probability p
+// requires ts to be sorted in descending order of probabilities
 func topP(ts []token, p float32) []token {
 	if p == 1.0 {
 		return ts
@@ -109,37 +107,24 @@ func topP(ts []token, p float32) []token {
 	for i, t := range ts {
 		sum += t.value
 		if sum > float32(p) {
-			ts = ts[:i+1]
-			return ts
+			return ts[:i+1]
 		}
 	}
 
 	return ts
 }
 
-// minP limits tokens to those with cumulative probability p
+// minP filters tokens with probabilities >= p * max_prob
+// requires ts to be sorted in descending order of probabilities
 func minP(ts []token, p float32) []token {
-	if p == 1.0 {
-		return ts
-	}
+	maxProb := ts[0].value
 
-	maxProb := float32(math.Inf(-1))
-	for _, token := range ts {
-		if token.value > maxProb {
-			maxProb = token.value
+	threshold := maxProb * p
+
+	for i, t := range ts {
+		if t.value < threshold {
+			return ts[:i]
 		}
 	}
-
-	threshold := maxProb * float32(p)
-
-	// Filter tokens in-place
-	validTokens := ts[:0]
-	for i, token := range ts {
-		if token.value >= threshold {
-			validTokens = append(validTokens, ts[i])
-		}
-	}
-
-	ts = validTokens
 	return ts
 }

sample/transforms_test.go

@@ -34,17 +34,22 @@ func compareLogits(t *testing.T, name string, want []float32, got []token) {
 
 func TestTemperature(t *testing.T) {
 	input := []float32{1.0, 4.0, -2.0, 0.0}
-	got := temperature(toTokens(input), 0.5)
+	tokens := toTokens(input)
+	temperature(tokens, 0.5)
 	want := []float32{2.0, 8.0, -4.0, 0.0}
-	compareLogits(t, "temperature(0.5)", want, got)
+	compareLogits(t, "temperature(0.5)", want, tokens)
 
-	got = temperature(toTokens(input), 1.0)
+	input = []float32{1.0, 4.0, -2.0, 0.0}
+	tokens = toTokens(input)
+	temperature(tokens, 1.0)
 	want = []float32{1.0, 4.0, -2.0, 0.0}
-	compareLogits(t, "temperature(1)", want, got)
+	compareLogits(t, "temperature(1)", want, tokens)
 
-	got = temperature(toTokens(input), 0.0)
+	input = []float32{1.0, 4.0, -2.0, 0.0}
+	tokens = toTokens(input)
+	temperature(tokens, 0.0)
 	want = []float32{1e7, 4e7, -2e7, 0.0}
-	compareLogits(t, "temperature(0)", want, got)
+	compareLogits(t, "temperature(0)", want, tokens)
 }
 
 func TestSoftmax(t *testing.T) {
@@ -90,16 +95,17 @@ func TestSoftmax(t *testing.T) {
 
 	for _, tt := range tests {
 		t.Run(tt.name, func(t *testing.T) {
-			got := softmax(toTokens(tt.input))
+			tokens := toTokens(tt.input)
+			softmax(tokens)
 
 			if tt.expected != nil {
-				compareLogits(t, tt.name, tt.expected, got)
+				compareLogits(t, tt.name, tt.expected, tokens)
 				return
 			}
 
 			// Check probabilities sum to 1
 			var sum float32
-			for _, token := range got {
+			for _, token := range tokens {
 				sum += token.value
 				if token.value < 0 || token.value > 1 {
 					t.Errorf("probability out of range [0,1]: got %f", token.value)
@@ -114,38 +120,44 @@ func TestSoftmax(t *testing.T) {
 
 func TestTopK(t *testing.T) {
 	input := []float32{0.026986899, 0.043722924, 0.036774673, 0.27755088, 0.0046718004, 0.08582123, 0.20409796, 0.00412893, 0.15720603, 0.045046154, 0.0030491839, 0.01681367}
-
-	// Test k=5
-	got := topK(toTokens(input), 5)
-	if len(got) != 5 {
-		t.Errorf("topK(5): wrong length: want 5, got %d", len(got))
+	tokens := toTokens(input)
+	tokens = topK(tokens, 5)
+	if len(tokens) != 5 {
+		t.Errorf("topK(5): wrong length: want 5, got %d", len(tokens))
 	}
-	// Should keep highest 3 values in descending order
 	want := []float32{0.27755088, 0.20409796, 0.15720603, 0.08582123, 0.045046154}
-	compareLogits(t, "topK(3)", want, got)
+	compareLogits(t, "topK(3)", want, tokens)
 
-	got = topK(toTokens(input), 20)
-	if len(got) != len(input) {
-		t.Errorf("topK(20): wrong length: want %d, got %d", len(input), len(got))
+	tokens = toTokens(input)
+	tokens = topK(tokens, 20)
+	if len(tokens) != len(input) {
+		t.Errorf("topK(20): wrong length: want %d, got %d", len(input), len(tokens))
 	}
 
-	// Test k=-1
 	input = []float32{0.026986899, 0.043722924, 0.036774673, 0.27755088, 0.0046718004, 0.08582123, 0.20409796, 0.00412893, 0.15720603, 0.045046154, 0.0030491839, 0.01681367}
 	want = []float32{0.27755088, 0.20409796, 0.15720603, 0.08582123, 0.045046154, 0.043722924, 0.036774673, 0.026986899, 0.01681367, 0.0046718004, 0.00412893, 0.0030491839}
-	got = topK(toTokens(input), -1)
-	if len(got) != len(input) {
-		t.Errorf("topK(-1): wrong length: want %d, got %d", len(input), len(got))
+	tokens = toTokens(input)
+	tokens = topK(tokens, -1)
+	if len(tokens) != len(input) {
+		t.Errorf("topK(-1): wrong length: want %d, got %d", len(input), len(tokens))
 	}
-	compareLogits(t, "topK(-1)", want, got)
+	compareLogits(t, "topK(-1)", want, tokens)
 
-	// Test k=0
 	input = []float32{0.026986899, 0.043722924, 0.036774673, 0.27755088, 0.0046718004, 0.08582123, 0.20409796, 0.00412893, 0.15720603, 0.045046154, 0.0030491839, 0.01681367}
 	want = []float32{0.27755088, 0.20409796, 0.15720603, 0.08582123, 0.045046154, 0.043722924, 0.036774673, 0.026986899, 0.01681367, 0.0046718004, 0.00412893, 0.0030491839}
-	got = topK(toTokens(input), 0)
-	if len(got) != len(input) {
-		t.Errorf("topK(-1): wrong length: want %d, got %d", len(input), len(got))
+	tokens = toTokens(input)
+	tokens = topK(tokens, 0)
+	if len(tokens) != len(input) {
+		t.Errorf("topK(-1): wrong length: want %d, got %d", len(input), len(tokens))
+	}
+	compareLogits(t, "topK(-1)", want, tokens)
+
+	input = []float32{-1e7, -2e7, -3e7, -4e7}
+	tokens = toTokens(input)
+	tokens = topK(tokens, 1)
+	if len(tokens) < 1 {
+		t.Error("topK should keep at least one token")
 	}
-	compareLogits(t, "topK(-1)", want, got)
 }
 
 func TestTopP(t *testing.T) {
@@ -153,50 +165,134 @@ func TestTopP(t *testing.T) {
 	tokens := toTokens(input)
 
 	// First apply temperature and softmax to get probabilities
-	tokens = softmax(tokens)
+	softmax(tokens)
 	tokens = topK(tokens, 20)
 
-	// Then apply topP
-	got := topP(tokens, 0.95)
+	// Test with very high p value
+	got := topP(tokens, 1.0)
+
+	// Should keep all tokens since p is 1
+	if len(got) != len(input) {
+		t.Errorf("topP(1.0): should keep all tokens, got %d, want %d", len(got), len(input))
+	}
+
+	// Test with normal p value
+	got = topP(tokens, 0.95)
 
-	// Should keep tokens until cumsum > 0.95
 	if len(got) > 3 {
-		t.Errorf("topP(0.95): kept too many tokens: got %d", len(got))
+		t.Errorf("topP(0.95): kept too many tokens: got %d", len(tokens))
+		t.Logf("got: %v", got)
+	}
+
+	// Test edge case - ensure at least one token remains
+	input = []float32{-1e6, -1e6, -1e7}
+	tokens = toTokens(input)
+	tokens = topK(tokens, 20)
+	softmax(tokens)
+	got = topP(tokens, 0.0)
+	if len(got) < 1 {
+		t.Error("topP should keep at least one token")
+	}
+
+	// Test with zero p value
+	got = topP(tokens, 0.0)
+
+	// Should keep only the highest probability token
+	if len(got) != 1 {
+		t.Errorf("topP(0.0): should keep only one token, got %d", len(got))
+		t.Logf("got: %v", got)
+	}
+
+	tokens = toTokens(input)
+	tokens = topK(tokens, 20)
+	softmax(tokens)
+	got = topP(tokens, 1e-10)
+	if len(got) == 0 {
+		t.Errorf("topP(1e-10): should keep at least one token, got %d", len(got))
 		t.Logf("got: %v", got)
 	}
 }
 
 func TestMinP(t *testing.T) {
-	input := []float32{-3, -2, -1, 0, 1, 2, 4, 3}
+	input := []float32{-2, 0, -1, -3, 2, 1, 4, 3}
 	tokens := toTokens(input)
 
 	// First apply temperature and softmax
-	tokens = softmax(tokens)
+	tokens = topK(tokens, 20)
+	softmax(tokens)
 
-	// Then apply minP
-	got := minP(tokens, 0.2)
+	tokens = minP(tokens, 1.0)
+
+	if len(tokens) != 1 {
+		t.Errorf("minP(1.0): should keep all tokens, got %d, want %d", len(tokens), len(tokens))
+	}
+
+	// Test with normal p value
+	tokens = toTokens(input) // Reset tokens
+	tokens = topK(tokens, 20)
+	softmax(tokens)
+	tokens = minP(tokens, 0.2)
 
 	// Should keep tokens with prob >= 0.2 * max_prob
-	if len(got) > 3 {
-		t.Errorf("minP(0.2): kept too many tokens: got %d", len(got))
+	if len(tokens) > 3 {
+		t.Errorf("minP(0.2): kept too many tokens: got %d", len(tokens))
+		t.Logf("got: %v", tokens)
 	}
-}
-
-func TestSortLogits(t *testing.T) {
-	input := []float32{0.026986899, 0.043722924, 0.036774673, 0.27755088, 0.0046718004, 0.08582123, 0.20409796, 0.00412893, 0.15720603, 0.045046154, 0.0030491839, 0.01681367}
-	tokens := toTokens(input)
 
+	// Test with zero p value
+	tokens = toTokens(input) // Reset tokens
 	tokens = topK(tokens, 20)
+	softmax(tokens)
+	tokens = minP(tokens, 0.0)
 
-	for i := 1; i < len(tokens); i++ {
-		if tokens[i].value > tokens[i-1].value {
-			t.Errorf("sortLogits: tokens not sorted in descending order at index %d: %f > %f",
-				i, tokens[i].value, tokens[i-1].value)
+	// Should keep only the highest probability token
+	if len(tokens) != len(input) {
+		t.Errorf("minP(0.0): should keep only one token, got %d", len(tokens))
+		t.Logf("got: %v", tokens)
+	}
+
+	// Test with single token
+	tokens = toTokens(input[:1])
+	tokens = topK(tokens, 20)
+	softmax(tokens)
+	tokens = minP(tokens, 0.1)
+
+	// Should keep only the highest probability token
+	if len(tokens) != 1 {
+		t.Errorf("minP(0.1): should return single token, got %d", len(tokens))
+		t.Logf("got: %v", tokens)
+	}
+
+	input = []float32{1e-10, 1e-10, 1e-10}
+	tokens = toTokens(input)
+	softmax(tokens)
+	tokens = minP(tokens, 1.0)
+	if len(tokens) < 1 {
+		t.Error("minP should keep at least one token even with extreme probabilities")
+		got := minP(tokens, 1.0)
+
+		if len(got) != 1 {
+			t.Errorf("minP(1.0): should keep all tokens, got %d, want %d", len(got), len(tokens))
+		}
+
+		// Test with normal p value
+		got = minP(tokens, 0.2)
+
+		// Should keep tokens with prob >= 0.2 * max_prob
+		if len(got) > 3 {
+			t.Errorf("minP(0.2): kept too many tokens: got %d", len(got))
+			t.Logf("got: %v", got)
+		}
+
+		// Test with zero p value
+		got = minP(tokens, 0.0)
+
+		// Should keep only the highest probability token
+		if len(got) != len(tokens) {
+			t.Errorf("minP(0.0): should keep only one token, got %d", len(got))
+			t.Logf("got: %v", got)
 		}
 	}
-
-	want := []float32{0.27755088, 0.20409796, 0.15720603, 0.08582123, 0.045046154, 0.043722924, 0.036774673, 0.026986899, 0.01681367, 0.0046718004, 0.00412893, 0.0030491839}
-	compareLogits(t, "sortLogits", want, tokens)
 }
 
 func BenchmarkTransforms(b *testing.B) {
@@ -231,7 +327,7 @@ func BenchmarkTransforms(b *testing.B) {
 		b.ResetTimer()
 		for b.Loop() {
 			copy(tokensCopy, tokens)
-			topK(tokensCopy, 10)
+			tokens = topK(tokensCopy, 10)
 		}
 	})
 
@@ -239,7 +335,7 @@ func BenchmarkTransforms(b *testing.B) {
 		b.ResetTimer()
 		for b.Loop() {
 			copy(tokensCopy, tokens)
-			topP(tokensCopy, 0.9)
+			tokens = topP(tokensCopy, 0.9)
 		}
 	})
 
@@ -247,7 +343,7 @@ func BenchmarkTransforms(b *testing.B) {
 		b.ResetTimer()
 		for b.Loop() {
 			copy(tokensCopy, tokens)
-			minP(tokensCopy, 0.2)
+			tokens = minP(tokensCopy, 0.2)
 		}
 	})
 
@@ -255,7 +351,7 @@ func BenchmarkTransforms(b *testing.B) {
 		b.ResetTimer()
 		for b.Loop() {
 			copy(tokensCopy, tokens)
-			topK(tokensCopy, 200000)
+			tokens = topK(tokensCopy, 200000)
 		}
 	})
 }

scripts/build_darwin.sh

@@ -8,7 +8,7 @@ usage() {
     exit 1
 }
 
-export VERSION=${VERSION:-$(git describe --tags --dirty)}
+export VERSION=${VERSION:-$(git describe --tags --first-parent --abbrev=7 --long --dirty --always | sed -e "s/^v//g")}
 export GOFLAGS="'-ldflags=-w -s \"-X=github.com/ollama/ollama/version.Version=${VERSION#v}\" \"-X=github.com/ollama/ollama/server.mode=release\"'"
 export CGO_CPPFLAGS='-mmacosx-version-min=11.3'
 

server/download.go

@@ -29,8 +29,9 @@ import (
 const maxRetries = 6
 
 var (
-	errMaxRetriesExceeded = errors.New("max retries exceeded")
-	errPartStalled        = errors.New("part stalled")
+	errMaxRetriesExceeded   = errors.New("max retries exceeded")
+	errPartStalled          = errors.New("part stalled")
+	errMaxRedirectsExceeded = errors.New("maximum redirects exceeded (10) for directURL")
 )
 
 var blobDownloadManager sync.Map
@@ -236,7 +237,7 @@ func (b *blobDownload) run(ctx context.Context, requestURL *url.URL, opts *regis
 
 			newOpts.CheckRedirect = func(req *http.Request, via []*http.Request) error {
 				if len(via) > 10 {
-					return errors.New("maximum redirects exceeded (10) for directURL")
+					return errMaxRedirectsExceeded
 				}
 
 				// if the hostname is the same, allow the redirect

server/images.go

@@ -35,14 +35,9 @@ var (
 	errCapabilityCompletion = errors.New("completion")
 	errCapabilityTools      = errors.New("tools")
 	errCapabilityInsert     = errors.New("insert")
-)
-
-type Capability string
-
-const (
-	CapabilityCompletion = Capability("completion")
-	CapabilityTools      = Capability("tools")
-	CapabilityInsert     = Capability("insert")
+	errCapabilityVision     = errors.New("vision")
+	errCapabilityEmbedding  = errors.New("embedding")
+	errInsecureProtocol     = errors.New("insecure protocol http")
 )
 
 type registryOptions struct {
@@ -65,52 +60,83 @@ type Model struct {
 	System         string
 	License        []string
 	Digest         string
-	Options        map[string]interface{}
+	Options        map[string]any
 	Messages       []api.Message
 
 	Template *template.Template
 }
 
+// Capabilities returns the capabilities that the model supports
+func (m *Model) Capabilities() []model.Capability {
+	capabilities := []model.Capability{}
+
+	// Check for completion capability
+	r, err := os.Open(m.ModelPath)
+	if err == nil {
+		defer r.Close()
+
+		f, _, err := ggml.Decode(r, 0)
+		if err == nil {
+			if _, ok := f.KV()[fmt.Sprintf("%s.pooling_type", f.KV().Architecture())]; ok {
+				capabilities = append(capabilities, model.CapabilityEmbedding)
+			} else {
+				capabilities = append(capabilities, model.CapabilityCompletion)
+			}
+			if _, ok := f.KV()[fmt.Sprintf("%s.vision.block_count", f.KV().Architecture())]; ok {
+				capabilities = append(capabilities, model.CapabilityVision)
+			}
+		} else {
+			slog.Error("couldn't decode ggml", "error", err)
+		}
+	} else {
+		slog.Error("couldn't open model file", "error", err)
+	}
+
+	if m.Template == nil {
+		return capabilities
+	}
+
+	// Check for tools capability
+	if slices.Contains(m.Template.Vars(), "tools") {
+		capabilities = append(capabilities, model.CapabilityTools)
+	}
+
+	// Check for insert capability
+	if slices.Contains(m.Template.Vars(), "suffix") {
+		capabilities = append(capabilities, model.CapabilityInsert)
+	}
+
+	return capabilities
+}
+
 // CheckCapabilities checks if the model has the specified capabilities returning an error describing
 // any missing or unknown capabilities
-func (m *Model) CheckCapabilities(caps ...Capability) error {
+func (m *Model) CheckCapabilities(want ...model.Capability) error {
+	available := m.Capabilities()
 	var errs []error
-	for _, cap := range caps {
-		switch cap {
-		case CapabilityCompletion:
-			r, err := os.Open(m.ModelPath)
-			if err != nil {
-				slog.Error("couldn't open model file", "error", err)
-				continue
-			}
-			defer r.Close()
 
-			// TODO(mxyng): decode the GGML into model to avoid doing this multiple times
-			f, _, err := ggml.Decode(r, 0)
-			if err != nil {
-				slog.Error("couldn't decode ggml", "error", err)
-				continue
-			}
+	// Map capabilities to their corresponding error
+	capToErr := map[model.Capability]error{
+		model.CapabilityCompletion: errCapabilityCompletion,
+		model.CapabilityTools:      errCapabilityTools,
+		model.CapabilityInsert:     errCapabilityInsert,
+		model.CapabilityVision:     errCapabilityVision,
+		model.CapabilityEmbedding:  errCapabilityEmbedding,
+	}
 
-			if _, ok := f.KV()[fmt.Sprintf("%s.pooling_type", f.KV().Architecture())]; ok {
-				errs = append(errs, errCapabilityCompletion)
-			}
-		case CapabilityTools:
-			if !slices.Contains(m.Template.Vars(), "tools") {
-				errs = append(errs, errCapabilityTools)
-			}
-		case CapabilityInsert:
-			vars := m.Template.Vars()
-			if !slices.Contains(vars, "suffix") {
-				errs = append(errs, errCapabilityInsert)
-			}
-		default:
+	for _, cap := range want {
+		err, ok := capToErr[cap]
+		if !ok {
 			slog.Error("unknown capability", "capability", cap)
 			return fmt.Errorf("unknown capability: %s", cap)
 		}
+
+		if !slices.Contains(available, cap) {
+			errs = append(errs, err)
+		}
 	}
 
-	if err := errors.Join(errs...); err != nil {
+	if len(errs) > 0 {
 		return fmt.Errorf("%w %w", errCapabilities, errors.Join(errs...))
 	}
 
@@ -479,7 +505,7 @@ func PushModel(ctx context.Context, name string, regOpts *registryOptions, fn fu
 	fn(api.ProgressResponse{Status: "retrieving manifest"})
 
 	if mp.ProtocolScheme == "http" && !regOpts.Insecure {
-		return errors.New("insecure protocol http")
+		return errInsecureProtocol
 	}
 
 	manifest, _, err := GetManifest(mp)
@@ -543,7 +569,7 @@ func PullModel(ctx context.Context, name string, regOpts *registryOptions, fn fu
 	}
 
 	if mp.ProtocolScheme == "http" && !regOpts.Insecure {
-		return errors.New("insecure protocol http")
+		return errInsecureProtocol
 	}
 
 	fn(api.ProgressResponse{Status: "pulling manifest"})

server/images_test.go

@@ -0,0 +1,360 @@
+package server
+
+import (
+	"bytes"
+	"encoding/binary"
+	"os"
+	"path/filepath"
+	"strings"
+	"testing"
+
+	"github.com/ollama/ollama/template"
+	"github.com/ollama/ollama/types/model"
+)
+
+// Constants for GGUF magic bytes and version
+var (
+	ggufMagic = []byte{0x47, 0x47, 0x55, 0x46} // "GGUF"
+	ggufVer   = uint32(3)                      // Version 3
+)
+
+// Helper function to create mock GGUF data
+func createMockGGUFData(architecture string, vision bool) []byte {
+	var buf bytes.Buffer
+
+	// Write GGUF header
+	buf.Write(ggufMagic)
+	binary.Write(&buf, binary.LittleEndian, ggufVer)
+
+	// Write tensor count (0 for our test)
+	var numTensors uint64 = 0
+	binary.Write(&buf, binary.LittleEndian, numTensors)
+
+	// Calculate number of metadata entries
+	numMetaEntries := uint64(1) // architecture entry
+	if vision {
+		numMetaEntries++
+	}
+	// Add embedding entry if architecture is "bert"
+	if architecture == "bert" {
+		numMetaEntries++
+	}
+	binary.Write(&buf, binary.LittleEndian, numMetaEntries)
+
+	// Write architecture metadata
+	archKey := "general.architecture"
+	keyLen := uint64(len(archKey))
+	binary.Write(&buf, binary.LittleEndian, keyLen)
+	buf.WriteString(archKey)
+
+	// String type (8)
+	var strType uint32 = 8
+	binary.Write(&buf, binary.LittleEndian, strType)
+
+	// String length
+	strLen := uint64(len(architecture))
+	binary.Write(&buf, binary.LittleEndian, strLen)
+	buf.WriteString(architecture)
+
+	if vision {
+		visionKey := architecture + ".vision.block_count"
+		keyLen = uint64(len(visionKey))
+		binary.Write(&buf, binary.LittleEndian, keyLen)
+		buf.WriteString(visionKey)
+
+		// uint32 type (4)
+		var uint32Type uint32 = 4
+		binary.Write(&buf, binary.LittleEndian, uint32Type)
+
+		// uint32 value (1)
+		var countVal uint32 = 1
+		binary.Write(&buf, binary.LittleEndian, countVal)
+	}
+	// Write embedding metadata if architecture is "bert"
+	if architecture == "bert" {
+		poolKey := architecture + ".pooling_type"
+		keyLen = uint64(len(poolKey))
+		binary.Write(&buf, binary.LittleEndian, keyLen)
+		buf.WriteString(poolKey)
+
+		// uint32 type (4)
+		var uint32Type uint32 = 4
+		binary.Write(&buf, binary.LittleEndian, uint32Type)
+
+		// uint32 value (1)
+		var poolingVal uint32 = 1
+		binary.Write(&buf, binary.LittleEndian, poolingVal)
+	}
+
+	return buf.Bytes()
+}
+
+func TestModelCapabilities(t *testing.T) {
+	// Create a temporary directory for test files
+	tempDir, err := os.MkdirTemp("", "model_capabilities_test")
+	if err != nil {
+		t.Fatalf("Failed to create temp directory: %v", err)
+	}
+	defer os.RemoveAll(tempDir)
+
+	// Create different types of mock model files
+	completionModelPath := filepath.Join(tempDir, "model.bin")
+	visionModelPath := filepath.Join(tempDir, "vision_model.bin")
+	embeddingModelPath := filepath.Join(tempDir, "embedding_model.bin")
+	// Create a simple model file for tests that don't depend on GGUF content
+	simpleModelPath := filepath.Join(tempDir, "simple_model.bin")
+
+	err = os.WriteFile(completionModelPath, createMockGGUFData("llama", false), 0o644)
+	if err != nil {
+		t.Fatalf("Failed to create completion model file: %v", err)
+	}
+	err = os.WriteFile(visionModelPath, createMockGGUFData("llama", true), 0o644)
+	if err != nil {
+		t.Fatalf("Failed to create completion model file: %v", err)
+	}
+	err = os.WriteFile(embeddingModelPath, createMockGGUFData("bert", false), 0o644)
+	if err != nil {
+		t.Fatalf("Failed to create embedding model file: %v", err)
+	}
+	err = os.WriteFile(simpleModelPath, []byte("dummy model data"), 0o644)
+	if err != nil {
+		t.Fatalf("Failed to create simple model file: %v", err)
+	}
+
+	toolsInsertTemplate, err := template.Parse("{{ .prompt }}{{ if .tools }}{{ .tools }}{{ end }}{{ if .suffix }}{{ .suffix }}{{ end }}")
+	if err != nil {
+		t.Fatalf("Failed to parse template: %v", err)
+	}
+	chatTemplate, err := template.Parse("{{ .prompt }}")
+	if err != nil {
+		t.Fatalf("Failed to parse template: %v", err)
+	}
+	toolsTemplate, err := template.Parse("{{ .prompt }}{{ if .tools }}{{ .tools }}{{ end }}")
+	if err != nil {
+		t.Fatalf("Failed to parse template: %v", err)
+	}
+
+	testModels := []struct {
+		name         string
+		model        Model
+		expectedCaps []model.Capability
+	}{
+		{
+			name: "model with completion capability",
+			model: Model{
+				ModelPath: completionModelPath,
+				Template:  chatTemplate,
+			},
+			expectedCaps: []model.Capability{model.CapabilityCompletion},
+		},
+
+		{
+			name: "model with completion, tools, and insert capability",
+			model: Model{
+				ModelPath: completionModelPath,
+				Template:  toolsInsertTemplate,
+			},
+			expectedCaps: []model.Capability{model.CapabilityCompletion, model.CapabilityTools, model.CapabilityInsert},
+		},
+		{
+			name: "model with tools and insert capability",
+			model: Model{
+				ModelPath: simpleModelPath,
+				Template:  toolsInsertTemplate,
+			},
+			expectedCaps: []model.Capability{model.CapabilityTools, model.CapabilityInsert},
+		},
+		{
+			name: "model with tools capability",
+			model: Model{
+				ModelPath: simpleModelPath,
+				Template:  toolsTemplate,
+			},
+			expectedCaps: []model.Capability{model.CapabilityTools},
+		},
+		{
+			name: "model with vision capability",
+			model: Model{
+				ModelPath: visionModelPath,
+				Template:  chatTemplate,
+			},
+			expectedCaps: []model.Capability{model.CapabilityCompletion, model.CapabilityVision},
+		},
+		{
+			name: "model with vision, tools, and insert capability",
+			model: Model{
+				ModelPath: visionModelPath,
+				Template:  toolsInsertTemplate,
+			},
+			expectedCaps: []model.Capability{model.CapabilityCompletion, model.CapabilityVision, model.CapabilityTools, model.CapabilityInsert},
+		},
+		{
+			name: "model with embedding capability",
+			model: Model{
+				ModelPath: embeddingModelPath,
+				Template:  chatTemplate,
+			},
+			expectedCaps: []model.Capability{model.CapabilityEmbedding},
+		},
+	}
+
+	// compare two slices of model.Capability regardless of order
+	compareCapabilities := func(a, b []model.Capability) bool {
+		if len(a) != len(b) {
+			return false
+		}
+
+		aCount := make(map[model.Capability]int)
+		for _, cap := range a {
+			aCount[cap]++
+		}
+
+		bCount := make(map[model.Capability]int)
+		for _, cap := range b {
+			bCount[cap]++
+		}
+
+		for cap, count := range aCount {
+			if bCount[cap] != count {
+				return false
+			}
+		}
+
+		return true
+	}
+
+	for _, tt := range testModels {
+		t.Run(tt.name, func(t *testing.T) {
+			// Test Capabilities method
+			caps := tt.model.Capabilities()
+			if !compareCapabilities(caps, tt.expectedCaps) {
+				t.Errorf("Expected capabilities %v, got %v", tt.expectedCaps, caps)
+			}
+		})
+	}
+}
+
+func TestModelCheckCapabilities(t *testing.T) {
+	// Create a temporary directory for test files
+	tempDir, err := os.MkdirTemp("", "model_check_capabilities_test")
+	if err != nil {
+		t.Fatalf("Failed to create temp directory: %v", err)
+	}
+	defer os.RemoveAll(tempDir)
+
+	visionModelPath := filepath.Join(tempDir, "vision_model.bin")
+	simpleModelPath := filepath.Join(tempDir, "model.bin")
+	embeddingModelPath := filepath.Join(tempDir, "embedding_model.bin")
+
+	err = os.WriteFile(simpleModelPath, []byte("dummy model data"), 0o644)
+	if err != nil {
+		t.Fatalf("Failed to create simple model file: %v", err)
+	}
+	err = os.WriteFile(visionModelPath, createMockGGUFData("llama", true), 0o644)
+	if err != nil {
+		t.Fatalf("Failed to create vision model file: %v", err)
+	}
+	err = os.WriteFile(embeddingModelPath, createMockGGUFData("bert", false), 0o644)
+	if err != nil {
+		t.Fatalf("Failed to create embedding model file: %v", err)
+	}
+
+	toolsInsertTemplate, err := template.Parse("{{ .prompt }}{{ if .tools }}{{ .tools }}{{ end }}{{ if .suffix }}{{ .suffix }}{{ end }}")
+	if err != nil {
+		t.Fatalf("Failed to parse template: %v", err)
+	}
+	chatTemplate, err := template.Parse("{{ .prompt }}")
+	if err != nil {
+		t.Fatalf("Failed to parse template: %v", err)
+	}
+	toolsTemplate, err := template.Parse("{{ .prompt }}{{ if .tools }}{{ .tools }}{{ end }}")
+	if err != nil {
+		t.Fatalf("Failed to parse template: %v", err)
+	}
+
+	tests := []struct {
+		name           string
+		model          Model
+		checkCaps      []model.Capability
+		expectedErrMsg string
+	}{
+		{
+			name: "completion model without tools capability",
+			model: Model{
+				ModelPath: simpleModelPath,
+				Template:  chatTemplate,
+			},
+			checkCaps:      []model.Capability{model.CapabilityTools},
+			expectedErrMsg: "does not support tools",
+		},
+		{
+			name: "model with all needed capabilities",
+			model: Model{
+				ModelPath: simpleModelPath,
+				Template:  toolsInsertTemplate,
+			},
+			checkCaps: []model.Capability{model.CapabilityTools, model.CapabilityInsert},
+		},
+		{
+			name: "model missing insert capability",
+			model: Model{
+				ModelPath: simpleModelPath,
+				Template:  toolsTemplate,
+			},
+			checkCaps:      []model.Capability{model.CapabilityInsert},
+			expectedErrMsg: "does not support insert",
+		},
+		{
+			name: "model missing vision capability",
+			model: Model{
+				ModelPath: simpleModelPath,
+				Template:  toolsTemplate,
+			},
+			checkCaps:      []model.Capability{model.CapabilityVision},
+			expectedErrMsg: "does not support vision",
+		},
+		{
+			name: "model with vision capability",
+			model: Model{
+				ModelPath: visionModelPath,
+				Template:  chatTemplate,
+			},
+			checkCaps: []model.Capability{model.CapabilityVision},
+		},
+		{
+			name: "model with embedding capability",
+			model: Model{
+				ModelPath: embeddingModelPath,
+				Template:  chatTemplate,
+			},
+			checkCaps: []model.Capability{model.CapabilityEmbedding},
+		},
+		{
+			name: "unknown capability",
+			model: Model{
+				ModelPath: simpleModelPath,
+				Template:  chatTemplate,
+			},
+			checkCaps:      []model.Capability{"unknown"},
+			expectedErrMsg: "unknown capability",
+		},
+	}
+
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			// Test CheckCapabilities method
+			err := tt.model.CheckCapabilities(tt.checkCaps...)
+			if tt.expectedErrMsg == "" {
+				if err != nil {
+					t.Errorf("Expected no error, got: %v", err)
+				}
+			} else {
+				if err == nil {
+					t.Errorf("Expected error containing %q, got nil", tt.expectedErrMsg)
+				} else if !strings.Contains(err.Error(), tt.expectedErrMsg) {
+					t.Errorf("Expected error containing %q, got: %v", tt.expectedErrMsg, err)
+				}
+			}
+		})
+	}
+}

server/internal/client/ollama/registry.go

@@ -25,6 +25,7 @@ import (
 	"os"
 	"path/filepath"
 	"runtime"
+	"runtime/debug"
 	"slices"
 	"strconv"
 	"strings"
@@ -36,7 +37,6 @@ import (
 	"golang.org/x/sync/errgroup"
 
 	"github.com/ollama/ollama/server/internal/cache/blob"
-	"github.com/ollama/ollama/server/internal/internal/backoff"
 	"github.com/ollama/ollama/server/internal/internal/names"
 
 	_ "embed"
@@ -59,6 +59,11 @@ var (
 	// ErrCached is passed to [Trace.PushUpdate] when a layer already
 	// exists. It is a non-fatal error and is never returned by [Registry.Push].
 	ErrCached = errors.New("cached")
+
+	// ErrIncomplete is returned by [Registry.Pull] when a model pull was
+	// incomplete due to one or more layer download failures. Users that
+	// want specific errors should use [WithTrace].
+	ErrIncomplete = errors.New("incomplete")
 )
 
 // Defaults
@@ -212,12 +217,6 @@ type Registry struct {
 	// request. If zero, [DefaultChunkingThreshold] is used.
 	ChunkingThreshold int64
 
-	// MaxChunkSize is the maximum size of a chunk to download. If zero,
-	// the default is [DefaultMaxChunkSize].
-	//
-	// It is only used when a layer is larger than [MaxChunkingThreshold].
-	MaxChunkSize int64
-
 	// Mask, if set, is the name used to convert non-fully qualified names
 	// to fully qualified names. If empty, [DefaultMask] is used.
 	Mask string
@@ -259,6 +258,7 @@ func DefaultRegistry() (*Registry, error) {
 	}
 
 	var rc Registry
+	rc.UserAgent = UserAgent()
 	rc.Key, err = ssh.ParseRawPrivateKey(keyPEM)
 	if err != nil {
 		return nil, err
@@ -274,6 +274,27 @@ func DefaultRegistry() (*Registry, error) {
 	return &rc, nil
 }
 
+func UserAgent() string {
+	buildinfo, _ := debug.ReadBuildInfo()
+
+	version := buildinfo.Main.Version
+	if version == "(devel)" {
+		// When using `go run .` the version is "(devel)". This is seen
+		// as an invalid version by ollama.com and so it defaults to
+		// "needs upgrade" for some requests, such as pulls. These
+		// checks can be skipped by using the special version "v0.0.0",
+		// so we set it to that here.
+		version = "v0.0.0"
+	}
+
+	return fmt.Sprintf("ollama/%s (%s %s) Go/%s",
+		version,
+		runtime.GOARCH,
+		runtime.GOOS,
+		runtime.Version(),
+	)
+}
+
 func (r *Registry) maxStreams() int {
 	return cmp.Or(r.MaxStreams, runtime.GOMAXPROCS(0))
 }
@@ -400,26 +421,19 @@ func (r *Registry) Push(ctx context.Context, name string, p *PushParams) error {
 	return err
 }
 
-func canRetry(err error) bool {
-	var re *Error
-	if !errors.As(err, &re) {
-		return false
-	}
-	return re.Status >= 500
-}
-
 // trackingReader is an io.Reader that tracks the number of bytes read and
 // calls the update function with the layer, the number of bytes read.
 //
 // It always calls update with a nil error.
 type trackingReader struct {
-	r io.Reader
-	n *atomic.Int64
+	l      *Layer
+	r      io.Reader
+	update func(l *Layer, n int64, err error)
 }
 
 func (r *trackingReader) Read(p []byte) (n int, err error) {
 	n, err = r.r.Read(p)
-	r.n.Add(int64(n))
+	r.update(r.l, int64(n), nil)
 	return
 }
 
@@ -435,6 +449,11 @@ func (r *Registry) Pull(ctx context.Context, name string) error {
 	if err != nil {
 		return err
 	}
+
+	// TODO(bmizerany): decide if this should be considered valid. Maybe
+	// server-side we special case '{}' to have some special meaning? Maybe
+	// "archiving" a tag (which is how we reason about it in the registry
+	// already, just with a different twist).
 	if len(m.Layers) == 0 {
 		return fmt.Errorf("%w: no layers", ErrManifestInvalid)
 	}
@@ -444,11 +463,7 @@ func (r *Registry) Pull(ctx context.Context, name string) error {
 		return err
 	}
 
-	exists := func(l *Layer) bool {
-		info, err := c.Get(l.Digest)
-		return err == nil && info.Size == l.Size
-	}
-
+	// TODO(bmizerany): work to remove the need to do this
 	layers := m.Layers
 	if m.Config != nil && m.Config.Digest.IsValid() {
 		layers = append(layers, m.Config)
@@ -456,99 +471,124 @@ func (r *Registry) Pull(ctx context.Context, name string) error {
 
 	// Send initial layer trace events to allow clients to have an
 	// understanding of work to be done before work starts.
+	var expected int64
 	t := traceFromContext(ctx)
-	skip := make([]bool, len(layers))
-	for i, l := range layers {
+	for _, l := range layers {
 		t.update(l, 0, nil)
-		if exists(l) {
-			skip[i] = true
-			t.update(l, l.Size, ErrCached)
-		}
+		expected += l.Size
 	}
 
-	g, ctx := errgroup.WithContext(ctx)
+	var received atomic.Int64
+	var g errgroup.Group
 	g.SetLimit(r.maxStreams())
-	for i, l := range layers {
-		if skip[i] {
+	for _, l := range layers {
+		info, err := c.Get(l.Digest)
+		if err == nil && info.Size == l.Size {
+			received.Add(l.Size)
+			t.update(l, l.Size, ErrCached)
 			continue
 		}
 
+		var wg sync.WaitGroup
 		chunked, err := c.Chunked(l.Digest, l.Size)
 		if err != nil {
 			t.update(l, 0, err)
 			continue
 		}
-		defer chunked.Close()
 
-		var progress atomic.Int64
 		for cs, err := range r.chunksums(ctx, name, l) {
 			if err != nil {
-				t.update(l, progress.Load(), err)
+				// Chunksum stream interrupted. Note in trace
+				// log and let in-flight downloads complete.
+				// This will naturally trigger ErrIncomplete
+				// since received < expected bytes.
+				t.update(l, 0, err)
 				break
 			}
 
+			cacheKey := fmt.Sprintf(
+				"v1 pull chunksum %s %s %d-%d",
+				l.Digest,
+				cs.Digest,
+				cs.Chunk.Start,
+				cs.Chunk.End,
+			)
+			cacheKeyDigest := blob.DigestFromBytes(cacheKey)
+			_, err := c.Get(cacheKeyDigest)
+			if err == nil {
+				received.Add(cs.Chunk.Size())
+				t.update(l, cs.Chunk.Size(), ErrCached)
+				continue
+			}
+
+			wg.Add(1)
 			g.Go(func() (err error) {
-				defer func() { t.update(l, progress.Load(), err) }()
-
-				for _, err := range backoff.Loop(ctx, 3*time.Second) {
-					if err != nil {
-						return err
-					}
-					err := func() error {
-						req, err := http.NewRequestWithContext(ctx, "GET", cs.URL, nil)
-						if err != nil {
-							return err
-						}
-						req.Header.Set("Range", fmt.Sprintf("bytes=%d-%d", cs.Chunk.Start, cs.Chunk.End))
-						res, err := sendRequest(r.client(), req)
-						if err != nil {
-							return err
-						}
-						defer res.Body.Close()
-
-						// Count bytes towards
-						// progress, as they arrive, so
-						// that our bytes piggyback
-						// other chunk updates on
-						// completion.
+				defer func() {
+					if err == nil {
+						// Ignore cache key write errors for now. We've already
+						// reported to trace that the chunk is complete.
 						//
-						// This tactic is enough to
-						// show "smooth" progress given
-						// the current CLI client. In
-						// the near future, the server
-						// should report download rate
-						// since it knows better than
-						// a client that is measuring
-						// rate based on wall-clock
-						// time-since-last-update.
-						body := &trackingReader{r: res.Body, n: &progress}
+						// Ideally, we should only report completion to trace
+						// after successful cache commit. This current approach
+						// works but could trigger unnecessary redownloads if
+						// the checkpoint key is missing on next pull.
+						//
+						// Not incorrect, just suboptimal - fix this in a
+						// future update.
+						_ = blob.PutBytes(c, cacheKeyDigest, cacheKey)
 
-						err = chunked.Put(cs.Chunk, cs.Digest, body)
-						if err != nil {
-							return err
-						}
-
-						return nil
-					}()
-					if !canRetry(err) {
-						return err
+						received.Add(cs.Chunk.Size())
+					} else {
+						t.update(l, 0, err)
 					}
+					wg.Done()
+				}()
+
+				req, err := http.NewRequestWithContext(ctx, "GET", cs.URL, nil)
+				if err != nil {
+					return err
 				}
-				return nil
+				req.Header.Set("Range", fmt.Sprintf("bytes=%d-%d", cs.Chunk.Start, cs.Chunk.End))
+				res, err := sendRequest(r.client(), req)
+				if err != nil {
+					return err
+				}
+				defer res.Body.Close()
+
+				body := &trackingReader{l: l, r: res.Body, update: t.update}
+				return chunked.Put(cs.Chunk, cs.Digest, body)
 			})
 		}
+
+		// Close writer immediately after downloads finish, not at Pull
+		// exit. Using defer would keep file descriptors open until all
+		// layers complete, potentially exhausting system limits with
+		// many layers.
+		//
+		// The WaitGroup tracks when all chunks finish downloading,
+		// allowing precise writer closure in a background goroutine.
+		// Each layer briefly uses one extra goroutine while at most
+		// maxStreams()-1 chunks download in parallel.
+		//
+		// This caps file descriptors at maxStreams() instead of
+		// growing with layer count.
+		g.Go(func() error {
+			wg.Wait()
+			chunked.Close()
+			return nil
+		})
 	}
 	if err := g.Wait(); err != nil {
 		return err
 	}
+	if received.Load() != expected {
+		return fmt.Errorf("%w: received %d/%d bytes", ErrIncomplete, received.Load(), expected)
+	}
 
-	// store the manifest blob
 	md := blob.DigestFromBytes(m.Data)
 	if err := blob.PutBytes(c, md, m.Data); err != nil {
 		return err
 	}
-
-	// commit the manifest with a link
 	return c.Link(m.Name, md)
 }
 
@@ -587,6 +627,30 @@ func (m *Manifest) Layer(d blob.Digest) *Layer {
 	return nil
 }
 
+func (m *Manifest) All() iter.Seq[*Layer] {
+	return func(yield func(*Layer) bool) {
+		if !yield(m.Config) {
+			return
+		}
+		for _, l := range m.Layers {
+			if !yield(l) {
+				return
+			}
+		}
+	}
+}
+
+func (m *Manifest) Size() int64 {
+	var size int64
+	if m.Config != nil {
+		size += m.Config.Size
+	}
+	for _, l := range m.Layers {
+		size += l.Size
+	}
+	return size
+}
+
 // MarshalJSON implements json.Marshaler.
 //
 // NOTE: It adds an empty config object to the manifest, which is required by
@@ -729,20 +793,32 @@ func (r *Registry) chunksums(ctx context.Context, name string, l *Layer) iter.Se
 			return
 		}
 
-		// A chunksums response is a sequence of chunksums in a
-		// simple, easy to parse line-oriented format.
+		// The response is a sequence of chunksums.
 		//
-		// Example:
+		// Chunksums are chunks of a larger blob that can be
+		// downloaded and verified independently.
 		//
-		//     >> GET /v2/<namespace>/<model>/chunksums/<digest>
+		// The chunksums endpoint is a GET request that returns a
+		// sequence of chunksums in the following format:
 		//
-		//     << HTTP/1.1 200 OK
-		//     << Content-Location: <blobURL>
-		//     <<
-		//     << <digest> <start>-<end>
-		//     << ...
+		//     > GET /v2/<namespace>/<model>/chunksums/<digest>
 		//
-		// The blobURL is the URL to download the chunks from.
+		//     < HTTP/1.1 200 OK
+		//     < Content-Location: <blobURL>
+		//     <
+		//     < <digest> <start>-<end>
+		//     < ...
+		//
+		// The <blobURL> is the URL to download the chunks from and
+		// each <digest> is the digest of the chunk, and <start>-<end>
+		// is the range the chunk in the blob.
+		//
+		// Ranges may be used directly in Range headers like
+		// "bytes=<start>-<end>".
+		//
+		// The chunksums returned are guaranteed to be contiguous and
+		// include all bytes of the layer. If the stream is cut short,
+		// clients should retry.
 
 		chunksumsURL := fmt.Sprintf("%s://%s/v2/%s/%s/chunksums/%s",
 			scheme,

server/internal/client/ollama/registry_test.go

@@ -9,21 +9,41 @@ import (
 	"fmt"
 	"io"
 	"io/fs"
-	"math/rand/v2"
+	"net"
 	"net/http"
 	"net/http/httptest"
 	"os"
-	"path"
 	"reflect"
-	"slices"
 	"strings"
+	"sync/atomic"
 	"testing"
-	"time"
 
 	"github.com/ollama/ollama/server/internal/cache/blob"
 	"github.com/ollama/ollama/server/internal/testutil"
 )
 
+func ExampleRegistry_cancelOnFirstError() {
+	ctx, cancel := context.WithCancel(context.Background())
+	defer cancel()
+
+	ctx = WithTrace(ctx, &Trace{
+		Update: func(l *Layer, n int64, err error) {
+			if err != nil {
+				// Discontinue pulling layers if there is an
+				// error instead of continuing to pull more
+				// data.
+				cancel()
+			}
+		},
+	})
+
+	var r Registry
+	if err := r.Pull(ctx, "model"); err != nil {
+		// panic for demo purposes
+		panic(err)
+	}
+}
+
 func TestManifestMarshalJSON(t *testing.T) {
 	// All manifests should contain an "empty" config object.
 	var m Manifest
@@ -56,21 +76,21 @@ func (rr recordRoundTripper) RoundTrip(req *http.Request) (*http.Response, error
 
 // newClient constructs a cache with predefined manifests for testing. The manifests are:
 //
-//	empty: no data
-//	zero: no layers
-//	single: one layer with the contents "exists"
-//	multiple: two layers with the contents "exists" and "here"
-//	notfound: a layer that does not exist in the cache
-//	null: one null layer (e.g. [null])
-//	sizemismatch: one valid layer, and one with a size mismatch (file size is less than the reported size)
-//	invalid: a layer with invalid JSON data
+//	empty:         no data
+//	zero:          no layers
+//	single:        one layer with the contents "exists"
+//	multiple:      two layers with the contents "exists" and "here"
+//	notfound:      a layer that does not exist in the cache
+//	null:          one null layer (e.g. [null])
+//	sizemismatch:  one valid layer, and one with a size mismatch (file size is less than the reported size)
+//	invalid:       a layer with invalid JSON data
 //
 // Tests that want to ensure the client does not communicate with the upstream
 // registry should pass a nil handler, which will cause a panic if
 // communication is attempted.
 //
 // To simulate a network error, pass a handler that returns a 499 status code.
-func newClient(t *testing.T, h http.HandlerFunc) (*Registry, *blob.DiskCache) {
+func newClient(t *testing.T, upstreamRegistry http.HandlerFunc) (*Registry, *blob.DiskCache) {
 	t.Helper()
 
 	c, err := blob.Open(t.TempDir())
@@ -88,7 +108,7 @@ func newClient(t *testing.T, h http.HandlerFunc) (*Registry, *blob.DiskCache) {
 	r := &Registry{
 		Cache: c,
 		HTTPClient: &http.Client{
-			Transport: recordRoundTripper(h),
+			Transport: recordRoundTripper(upstreamRegistry),
 		},
 	}
 
@@ -315,15 +335,8 @@ func TestPushCommitRoundtripError(t *testing.T) {
 	}
 }
 
-func checkNotExist(t *testing.T, err error) {
-	t.Helper()
-	if !errors.Is(err, fs.ErrNotExist) {
-		t.Fatalf("err = %v; want fs.ErrNotExist", err)
-	}
-}
-
 func TestRegistryPullInvalidName(t *testing.T) {
-	rc, _ := newClient(t, nil)
+	rc, _ := newRegistryClient(t, nil)
 	err := rc.Pull(t.Context(), "://")
 	if !errors.Is(err, ErrNameInvalid) {
 		t.Errorf("err = %v; want %v", err, ErrNameInvalid)
@@ -339,197 +352,16 @@ func TestRegistryPullInvalidManifest(t *testing.T) {
 	}
 
 	for _, resp := range cases {
-		rc, _ := newClient(t, func(w http.ResponseWriter, r *http.Request) {
+		rc, _ := newRegistryClient(t, func(w http.ResponseWriter, r *http.Request) {
 			io.WriteString(w, resp)
 		})
-		err := rc.Pull(t.Context(), "x")
+		err := rc.Pull(t.Context(), "http://example.com/a/b")
 		if !errors.Is(err, ErrManifestInvalid) {
 			t.Errorf("err = %v; want invalid manifest", err)
 		}
 	}
 }
 
-func TestRegistryPullNotCached(t *testing.T) {
-	check := testutil.Checker(t)
-
-	var c *blob.DiskCache
-	var rc *Registry
-
-	d := blob.DigestFromBytes("some data")
-	rc, c = newClient(t, func(w http.ResponseWriter, r *http.Request) {
-		if strings.Contains(r.URL.Path, "/blobs/") {
-			io.WriteString(w, "some data")
-			return
-		}
-		fmt.Fprintf(w, `{"layers":[{"digest":%q,"size":9}]}`, d)
-	})
-
-	// Confirm that the layer does not exist locally
-	_, err := rc.ResolveLocal("model")
-	checkNotExist(t, err)
-
-	_, err = c.Get(d)
-	checkNotExist(t, err)
-
-	err = rc.Pull(t.Context(), "model")
-	check(err)
-
-	mw, err := rc.Resolve(t.Context(), "model")
-	check(err)
-	mg, err := rc.ResolveLocal("model")
-	check(err)
-	if !reflect.DeepEqual(mw, mg) {
-		t.Errorf("mw = %v; mg = %v", mw, mg)
-	}
-
-	// Confirm successful download
-	info, err := c.Get(d)
-	check(err)
-	if info.Digest != d {
-		t.Errorf("info.Digest = %v; want %v", info.Digest, d)
-	}
-	if info.Size != 9 {
-		t.Errorf("info.Size = %v; want %v", info.Size, 9)
-	}
-
-	data, err := os.ReadFile(c.GetFile(d))
-	check(err)
-	if string(data) != "some data" {
-		t.Errorf("data = %q; want %q", data, "exists")
-	}
-}
-
-func TestRegistryPullCached(t *testing.T) {
-	cached := blob.DigestFromBytes("exists")
-	rc, _ := newClient(t, func(w http.ResponseWriter, r *http.Request) {
-		if strings.Contains(r.URL.Path, "/blobs/") {
-			w.WriteHeader(499) // should not be called
-			return
-		}
-		if strings.Contains(r.URL.Path, "/manifests/") {
-			fmt.Fprintf(w, `{"layers":[{"digest":%q,"size":6}]}`, cached)
-		}
-	})
-
-	var errs []error
-	var reads []int64
-	ctx := WithTrace(t.Context(), &Trace{
-		Update: func(d *Layer, n int64, err error) {
-			t.Logf("update %v %d %v", d, n, err)
-			reads = append(reads, n)
-			errs = append(errs, err)
-		},
-	})
-
-	ctx, cancel := context.WithTimeout(ctx, 3*time.Second)
-	defer cancel()
-
-	err := rc.Pull(ctx, "single")
-	testutil.Check(t, err)
-
-	want := []int64{0, 6}
-	if !errors.Is(errors.Join(errs...), ErrCached) {
-		t.Errorf("errs = %v; want %v", errs, ErrCached)
-	}
-	if !slices.Equal(reads, want) {
-		t.Errorf("pairs = %v; want %v", reads, want)
-	}
-}
-
-func TestRegistryPullManifestNotFound(t *testing.T) {
-	rc, _ := newClient(t, func(w http.ResponseWriter, r *http.Request) {
-		w.WriteHeader(http.StatusNotFound)
-	})
-	err := rc.Pull(t.Context(), "notfound")
-	checkErrCode(t, err, 404, "")
-}
-
-func TestRegistryPullResolveRemoteError(t *testing.T) {
-	rc, _ := newClient(t, func(w http.ResponseWriter, r *http.Request) {
-		w.WriteHeader(http.StatusInternalServerError)
-		io.WriteString(w, `{"errors":[{"code":"an_error"}]}`)
-	})
-	err := rc.Pull(t.Context(), "single")
-	checkErrCode(t, err, 500, "an_error")
-}
-
-func TestRegistryPullResolveRoundtripError(t *testing.T) {
-	rc, _ := newClient(t, func(w http.ResponseWriter, r *http.Request) {
-		if strings.Contains(r.URL.Path, "/manifests/") {
-			w.WriteHeader(499) // force RoundTrip error
-			return
-		}
-	})
-	err := rc.Pull(t.Context(), "single")
-	if !errors.Is(err, errRoundTrip) {
-		t.Errorf("err = %v; want %v", err, errRoundTrip)
-	}
-}
-
-// TestRegistryPullMixedCachedNotCached tests that cached layers do not
-// interfere with pulling layers that are not cached
-func TestRegistryPullMixedCachedNotCached(t *testing.T) {
-	x := blob.DigestFromBytes("xxxxxx")
-	e := blob.DigestFromBytes("exists")
-	y := blob.DigestFromBytes("yyyyyy")
-
-	for i := range 10 {
-		t.Logf("iteration %d", i)
-
-		digests := []blob.Digest{x, e, y}
-
-		rand.Shuffle(len(digests), func(i, j int) {
-			digests[i], digests[j] = digests[j], digests[i]
-		})
-
-		manifest := fmt.Sprintf(`{
-			"layers": [
-				{"digest":"%s","size":6},
-				{"digest":"%s","size":6},
-				{"digest":"%s","size":6}
-			]
-		}`, digests[0], digests[1], digests[2])
-
-		rc, c := newClient(t, func(w http.ResponseWriter, r *http.Request) {
-			switch path.Base(r.URL.Path) {
-			case "latest":
-				io.WriteString(w, manifest)
-			case x.String():
-				io.WriteString(w, "xxxxxx")
-			case e.String():
-				io.WriteString(w, "exists")
-			case y.String():
-				io.WriteString(w, "yyyyyy")
-			default:
-				panic(fmt.Sprintf("unexpected request: %v", r))
-			}
-		})
-
-		ctx := WithTrace(t.Context(), &Trace{
-			Update: func(l *Layer, n int64, err error) {
-				t.Logf("update %v %d %v", l, n, err)
-			},
-		})
-
-		// Check that we pull all layers that we can.
-
-		err := rc.Pull(ctx, "mixed")
-		if err != nil {
-			t.Fatal(err)
-		}
-
-		for _, d := range digests {
-			info, err := c.Get(d)
-			if err != nil {
-				t.Fatalf("Get(%v): %v", d, err)
-			}
-			if info.Size != 6 {
-				t.Errorf("info.Size = %v; want %v", info.Size, 6)
-			}
-		}
-	}
-}
-
 func TestRegistryResolveByDigest(t *testing.T) {
 	check := testutil.Checker(t)
 
@@ -567,26 +399,6 @@ func TestInsecureSkipVerify(t *testing.T) {
 	testutil.Check(t, err)
 }
 
-func TestCanRetry(t *testing.T) {
-	cases := []struct {
-		err  error
-		want bool
-	}{
-		{nil, false},
-		{errors.New("x"), false},
-		{ErrCached, false},
-		{ErrManifestInvalid, false},
-		{ErrNameInvalid, false},
-		{&Error{Status: 100}, false},
-		{&Error{Status: 500}, true},
-	}
-	for _, tt := range cases {
-		if got := canRetry(tt.err); got != tt.want {
-			t.Errorf("CanRetry(%v) = %v; want %v", tt.err, got, tt.want)
-		}
-	}
-}
-
 func TestErrorUnmarshal(t *testing.T) {
 	cases := []struct {
 		name    string
@@ -738,17 +550,23 @@ func TestParseNameExtended(t *testing.T) {
 
 func TestUnlink(t *testing.T) {
 	t.Run("found by name", func(t *testing.T) {
-		rc, _ := newClient(t, nil)
+		check := testutil.Checker(t)
+
+		rc, _ := newRegistryClient(t, nil)
+		// make a blob and link it
+		d := blob.DigestFromBytes("{}")
+		err := blob.PutBytes(rc.Cache, d, "{}")
+		check(err)
+		err = rc.Cache.Link("registry.ollama.ai/library/single:latest", d)
+		check(err)
 
 		// confirm linked
-		_, err := rc.ResolveLocal("single")
-		if err != nil {
-			t.Errorf("unexpected error: %v", err)
-		}
+		_, err = rc.ResolveLocal("single")
+		check(err)
 
 		// unlink
 		_, err = rc.Unlink("single")
-		testutil.Check(t, err)
+		check(err)
 
 		// confirm unlinked
 		_, err = rc.ResolveLocal("single")
@@ -757,7 +575,7 @@ func TestUnlink(t *testing.T) {
 		}
 	})
 	t.Run("not found by name", func(t *testing.T) {
-		rc, _ := newClient(t, nil)
+		rc, _ := newRegistryClient(t, nil)
 		ok, err := rc.Unlink("manifestNotFound")
 		if err != nil {
 			t.Fatal(err)
@@ -767,3 +585,369 @@ func TestUnlink(t *testing.T) {
 		}
 	})
 }
+
+// Many tests from here out, in this file are based on a single blob, "abc",
+// with the checksum of its sha256 hash. The checksum is:
+//
+//	"abc" -> sha256:ba7816bf8f01cfea414140de5dae2223b00361a396177a9cb410ff61f20015ad
+//
+// Using the literal value instead of a constant with fmt.Xprintf calls proved
+// to be the most readable and maintainable approach. The sum is consistently
+// used in the tests and unique so searches do not yield false positives.
+
+func checkRequest(t *testing.T, req *http.Request, method, path string) {
+	t.Helper()
+	if got := req.URL.Path; got != path {
+		t.Errorf("URL = %q, want %q", got, path)
+	}
+	if req.Method != method {
+		t.Errorf("Method = %q, want %q", req.Method, method)
+	}
+}
+
+func newRegistryClient(t *testing.T, h http.HandlerFunc) (*Registry, context.Context) {
+	s := httptest.NewServer(h)
+	t.Cleanup(s.Close)
+	cache, err := blob.Open(t.TempDir())
+	if err != nil {
+		t.Fatal(err)
+	}
+
+	ctx := WithTrace(t.Context(), &Trace{
+		Update: func(l *Layer, n int64, err error) {
+			t.Log("trace:", l.Digest.Short(), n, err)
+		},
+	})
+
+	rc := &Registry{
+		Cache: cache,
+		HTTPClient: &http.Client{Transport: &http.Transport{
+			Dial: func(network, addr string) (net.Conn, error) {
+				return net.Dial(network, s.Listener.Addr().String())
+			},
+		}},
+	}
+	return rc, ctx
+}
+
+func TestPullChunked(t *testing.T) {
+	var steps atomic.Int64
+	c, ctx := newRegistryClient(t, func(w http.ResponseWriter, r *http.Request) {
+		switch steps.Add(1) {
+		case 1:
+			checkRequest(t, r, "GET", "/v2/library/abc/manifests/latest")
+			io.WriteString(w, `{"layers":[{"size":3,"digest":"sha256:ba7816bf8f01cfea414140de5dae2223b00361a396177a9cb410ff61f20015ad"}]}`)
+		case 2:
+			checkRequest(t, r, "GET", "/v2/library/abc/chunksums/sha256:ba7816bf8f01cfea414140de5dae2223b00361a396177a9cb410ff61f20015ad")
+			w.Header().Set("Content-Location", "http://blob.store/v2/library/abc/blobs/sha256:ba7816bf8f01cfea414140de5dae2223b00361a396177a9cb410ff61f20015ad")
+			fmt.Fprintf(w, "%s 0-1\n", blob.DigestFromBytes("ab"))
+			fmt.Fprintf(w, "%s 2-2\n", blob.DigestFromBytes("c"))
+		case 3, 4:
+			checkRequest(t, r, "GET", "/v2/library/abc/blobs/sha256:ba7816bf8f01cfea414140de5dae2223b00361a396177a9cb410ff61f20015ad")
+			switch rng := r.Header.Get("Range"); rng {
+			case "bytes=0-1":
+				io.WriteString(w, "ab")
+			case "bytes=2-2":
+				t.Logf("writing c")
+				io.WriteString(w, "c")
+			default:
+				t.Errorf("unexpected range %q", rng)
+			}
+		default:
+			t.Errorf("unexpected steps %d: %v", steps.Load(), r)
+			http.Error(w, "unexpected steps", http.StatusInternalServerError)
+		}
+	})
+
+	c.ChunkingThreshold = 1 // force chunking
+
+	err := c.Pull(ctx, "http://o.com/library/abc")
+	testutil.Check(t, err)
+
+	_, err = c.Cache.Resolve("o.com/library/abc:latest")
+	testutil.Check(t, err)
+
+	if g := steps.Load(); g != 4 {
+		t.Fatalf("got %d steps, want 4", g)
+	}
+}
+
+func TestPullCached(t *testing.T) {
+	c, ctx := newRegistryClient(t, func(w http.ResponseWriter, r *http.Request) {
+		checkRequest(t, r, "GET", "/v2/library/abc/manifests/latest")
+		io.WriteString(w, `{"layers":[{"size":3,"digest":"sha256:ba7816bf8f01cfea414140de5dae2223b00361a396177a9cb410ff61f20015ad"}]}`)
+	})
+
+	check := testutil.Checker(t)
+
+	// Premeptively cache the blob
+	d, err := blob.ParseDigest("sha256:ba7816bf8f01cfea414140de5dae2223b00361a396177a9cb410ff61f20015ad")
+	check(err)
+	err = blob.PutBytes(c.Cache, d, []byte("abc"))
+	check(err)
+
+	// Pull only the manifest, which should be enough to resolve the cached blob
+	err = c.Pull(ctx, "http://o.com/library/abc")
+	check(err)
+}
+
+func TestPullManifestError(t *testing.T) {
+	c, ctx := newRegistryClient(t, func(w http.ResponseWriter, r *http.Request) {
+		checkRequest(t, r, "GET", "/v2/library/abc/manifests/latest")
+		w.WriteHeader(http.StatusNotFound)
+		io.WriteString(w, `{"errors":[{"code":"MANIFEST_UNKNOWN"}]}`)
+	})
+
+	err := c.Pull(ctx, "http://o.com/library/abc")
+	if err == nil {
+		t.Fatalf("expected error")
+	}
+	var got *Error
+	if !errors.Is(err, ErrModelNotFound) {
+		t.Fatalf("err = %v, want %v", got, ErrModelNotFound)
+	}
+}
+
+func TestPullLayerError(t *testing.T) {
+	c, ctx := newRegistryClient(t, func(w http.ResponseWriter, r *http.Request) {
+		checkRequest(t, r, "GET", "/v2/library/abc/manifests/latest")
+		io.WriteString(w, `!`)
+	})
+
+	err := c.Pull(ctx, "http://o.com/library/abc")
+	if err == nil {
+		t.Fatalf("expected error")
+	}
+	var want *json.SyntaxError
+	if !errors.As(err, &want) {
+		t.Fatalf("err = %T, want %T", err, want)
+	}
+}
+
+func TestPullLayerChecksumError(t *testing.T) {
+	var step atomic.Int64
+	c, _ := newRegistryClient(t, func(w http.ResponseWriter, r *http.Request) {
+		switch step.Add(1) {
+		case 1:
+			checkRequest(t, r, "GET", "/v2/library/abc/manifests/latest")
+			io.WriteString(w, `{"layers":[{"size":3,"digest":"sha256:ba7816bf8f01cfea414140de5dae2223b00361a396177a9cb410ff61f20015ad"}]}`)
+		case 2:
+			checkRequest(t, r, "GET", "/v2/library/abc/chunksums/sha256:ba7816bf8f01cfea414140de5dae2223b00361a396177a9cb410ff61f20015ad")
+			w.Header().Set("Content-Location", "http://blob.store/v2/library/abc/blobs/sha256:ba7816bf8f01cfea414140de5dae2223b00361a396177a9cb410ff61f20015ad")
+			fmt.Fprintf(w, "%s 0-1\n", blob.DigestFromBytes("ab"))
+			fmt.Fprintf(w, "%s 2-2\n", blob.DigestFromBytes("c"))
+		case 3:
+			w.WriteHeader(http.StatusNotFound)
+			io.WriteString(w, `{"errors":[{"code":"BLOB_UNKNOWN"}]}`)
+		case 4:
+			io.WriteString(w, "c")
+		default:
+			t.Errorf("unexpected steps %d: %v", step.Load(), r)
+			http.Error(w, "unexpected steps", http.StatusInternalServerError)
+		}
+	})
+
+	c.MaxStreams = 1
+	c.ChunkingThreshold = 1 // force chunking
+
+	var written atomic.Int64
+	ctx := WithTrace(t.Context(), &Trace{
+		Update: func(l *Layer, n int64, err error) {
+			t.Log("trace:", l.Digest.Short(), n, err)
+			written.Add(n)
+		},
+	})
+
+	err := c.Pull(ctx, "http://o.com/library/abc")
+	var got *Error
+	if !errors.As(err, &got) || got.Code != "BLOB_UNKNOWN" {
+		t.Fatalf("err = %v, want %v", err, got)
+	}
+
+	if g := written.Load(); g != 1 {
+		t.Fatalf("wrote %d bytes, want 1", g)
+	}
+}
+
+func TestPullChunksumStreamError(t *testing.T) {
+	var step atomic.Int64
+	c, ctx := newRegistryClient(t, func(w http.ResponseWriter, r *http.Request) {
+		switch step.Add(1) {
+		case 1:
+			checkRequest(t, r, "GET", "/v2/library/abc/manifests/latest")
+			io.WriteString(w, `{"layers":[{"size":3,"digest":"sha256:ba7816bf8f01cfea414140de5dae2223b00361a396177a9cb410ff61f20015ad"}]}`)
+		case 2:
+			w.Header().Set("Content-Location", "http://blob.store/v2/library/abc/blobs/sha256:ba7816bf8f01cfea414140de5dae2223b00361a396177a9cb410ff61f20015ad")
+
+			// Write one valid chunksum and one invalid chunksum
+			fmt.Fprintf(w, "%s 0-1\n", blob.DigestFromBytes("ab")) // valid
+			fmt.Fprint(w, "sha256:!")                              // invalid
+		case 3:
+			io.WriteString(w, "ab")
+		default:
+			t.Errorf("unexpected steps %d: %v", step.Load(), r)
+			http.Error(w, "unexpected steps", http.StatusInternalServerError)
+		}
+	})
+
+	c.ChunkingThreshold = 1 // force chunking
+
+	got := c.Pull(ctx, "http://o.com/library/abc")
+	if !errors.Is(got, ErrIncomplete) {
+		t.Fatalf("err = %v, want %v", got, ErrIncomplete)
+	}
+}
+
+type flushAfterWriter struct {
+	w io.Writer
+}
+
+func (f *flushAfterWriter) Write(p []byte) (n int, err error) {
+	n, err = f.w.Write(p)
+	f.w.(http.Flusher).Flush() // panic if not a flusher
+	return
+}
+
+func TestPullChunksumStreaming(t *testing.T) {
+	csr, csw := io.Pipe()
+	defer csw.Close()
+
+	var step atomic.Int64
+	c, _ := newRegistryClient(t, func(w http.ResponseWriter, r *http.Request) {
+		switch step.Add(1) {
+		case 1:
+			checkRequest(t, r, "GET", "/v2/library/abc/manifests/latest")
+			io.WriteString(w, `{"layers":[{"size":3,"digest":"sha256:ba7816bf8f01cfea414140de5dae2223b00361a396177a9cb410ff61f20015ad"}]}`)
+		case 2:
+			w.Header().Set("Content-Location", "http://blob.store/v2/library/abc/blobs/sha256:ba7816bf8f01cfea414140de5dae2223b00361a396177a9cb410ff61f20015ad")
+			fw := &flushAfterWriter{w} // ensure client gets data as it arrives by aggressively flushing
+			_, err := io.Copy(fw, csr)
+			if err != nil {
+				t.Errorf("copy: %v", err)
+			}
+		case 3:
+			io.WriteString(w, "ab")
+		case 4:
+			io.WriteString(w, "c")
+		default:
+			t.Errorf("unexpected steps %d: %v", step.Load(), r)
+			http.Error(w, "unexpected steps", http.StatusInternalServerError)
+		}
+	})
+
+	c.ChunkingThreshold = 1 // force chunking
+
+	update := make(chan int64, 1)
+	ctx := WithTrace(t.Context(), &Trace{
+		Update: func(l *Layer, n int64, err error) {
+			t.Log("trace:", l.Digest.Short(), n, err)
+			if n > 0 {
+				update <- n
+			}
+		},
+	})
+
+	errc := make(chan error, 1)
+	go func() {
+		errc <- c.Pull(ctx, "http://o.com/library/abc")
+	}()
+
+	// Send first chunksum and ensure it kicks off work immediately
+	fmt.Fprintf(csw, "%s 0-1\n", blob.DigestFromBytes("ab"))
+	if g := <-update; g != 2 {
+		t.Fatalf("got %d, want 2", g)
+	}
+
+	// now send the second chunksum and ensure it kicks off work immediately
+	fmt.Fprintf(csw, "%s 2-2\n", blob.DigestFromBytes("c"))
+	if g := <-update; g != 1 {
+		t.Fatalf("got %d, want 1", g)
+	}
+	csw.Close()
+	testutil.Check(t, <-errc)
+}
+
+func TestPullChunksumsCached(t *testing.T) {
+	var step atomic.Int64
+	c, _ := newRegistryClient(t, func(w http.ResponseWriter, r *http.Request) {
+		switch step.Add(1) {
+		case 1:
+			checkRequest(t, r, "GET", "/v2/library/abc/manifests/latest")
+			io.WriteString(w, `{"layers":[{"size":3,"digest":"sha256:ba7816bf8f01cfea414140de5dae2223b00361a396177a9cb410ff61f20015ad"}]}`)
+		case 2:
+			w.Header().Set("Content-Location", "http://blob.store/v2/library/abc/blobs/sha256:ba7816bf8f01cfea414140de5dae2223b00361a396177a9cb410ff61f20015ad")
+			fmt.Fprintf(w, "%s 0-1\n", blob.DigestFromBytes("ab"))
+			fmt.Fprintf(w, "%s 2-2\n", blob.DigestFromBytes("c"))
+		case 3, 4:
+			switch rng := r.Header.Get("Range"); rng {
+			case "bytes=0-1":
+				io.WriteString(w, "ab")
+			case "bytes=2-2":
+				io.WriteString(w, "c")
+			default:
+				t.Errorf("unexpected range %q", rng)
+			}
+		default:
+			t.Errorf("unexpected steps %d: %v", step.Load(), r)
+			http.Error(w, "unexpected steps", http.StatusInternalServerError)
+		}
+	})
+
+	c.MaxStreams = 1        // force serial processing of chunksums
+	c.ChunkingThreshold = 1 // force chunking
+
+	ctx, cancel := context.WithCancel(t.Context())
+	defer cancel()
+
+	// Cancel the pull after the first chunksum is processed, but before
+	// the second chunksum is processed (which is waiting because
+	// MaxStreams=1). This should cause the second chunksum to error out
+	// leaving the blob incomplete.
+	ctx = WithTrace(ctx, &Trace{
+		Update: func(l *Layer, n int64, err error) {
+			if n > 0 {
+				cancel()
+			}
+		},
+	})
+	err := c.Pull(ctx, "http://o.com/library/abc")
+	if !errors.Is(err, context.Canceled) {
+		t.Fatalf("err = %v, want %v", err, context.Canceled)
+	}
+
+	_, err = c.Cache.Resolve("o.com/library/abc:latest")
+	if !errors.Is(err, fs.ErrNotExist) {
+		t.Fatalf("err = %v, want nil", err)
+	}
+
+	// Reset state and pull again to ensure the blob chunks that should
+	// have been cached are, and the remaining chunk was downloaded, making
+	// the blob complete.
+	step.Store(0)
+	var written atomic.Int64
+	var cached atomic.Int64
+	ctx = WithTrace(t.Context(), &Trace{
+		Update: func(l *Layer, n int64, err error) {
+			t.Log("trace:", l.Digest.Short(), n, err)
+			if errors.Is(err, ErrCached) {
+				cached.Add(n)
+			}
+			written.Add(n)
+		},
+	})
+
+	check := testutil.Checker(t)
+
+	err = c.Pull(ctx, "http://o.com/library/abc")
+	check(err)
+
+	_, err = c.Cache.Resolve("o.com/library/abc:latest")
+	check(err)
+
+	if g := written.Load(); g != 3 {
+		t.Fatalf("wrote %d bytes, want 3", g)
+	}
+	if g := cached.Load(); g != 2 { // "ab" should have been cached
+		t.Fatalf("cached %d bytes, want 3", g)
+	}
+}

server/internal/registry/server.go

@@ -200,7 +200,7 @@ type params struct {
 	//
 	// Unfortunately, this API was designed to be a bit awkward. Stream is
 	// defined to default to true if not present, so we need a way to check
-	// if the client decisively it to false. So, we use a pointer to a
+	// if the client decisively set it to false. So, we use a pointer to a
 	// bool. Gross.
 	//
 	// Use [stream()] to get the correct value for this field.
@@ -280,17 +280,17 @@ func (s *Local) handlePull(w http.ResponseWriter, r *http.Request) error {
 	progress := make(map[*ollama.Layer]int64)
 
 	progressCopy := make(map[*ollama.Layer]int64, len(progress))
-	pushUpdate := func() {
+	flushProgress := func() {
 		defer maybeFlush()
 
-		// TODO(bmizerany): This scales poorly with more layers due to
-		// needing to flush out them all in one big update. We _could_
-		// just flush on the changed ones, or just track the whole
-		// download. Needs more thought. This is fine for now.
+		// TODO(bmizerany): Flushing every layer in one update doesn't
+		// scale well. We could flush only the modified layers or track
+		// the full download. Needs further consideration, though it's
+		// fine for now.
 		mu.Lock()
 		maps.Copy(progressCopy, progress)
 		mu.Unlock()
-		for l, n := range progress {
+		for l, n := range progressCopy {
 			enc.Encode(progressUpdateJSON{
 				Digest:    l.Digest,
 				Total:     l.Size,
@@ -298,19 +298,26 @@ func (s *Local) handlePull(w http.ResponseWriter, r *http.Request) error {
 			})
 		}
 	}
+	defer flushProgress()
 
-	t := time.NewTicker(time.Hour) // "unstarted" timer
+	t := time.NewTicker(1000 * time.Hour) // "unstarted" timer
 	start := sync.OnceFunc(func() {
-		pushUpdate()
+		flushProgress() // flush initial state
 		t.Reset(100 * time.Millisecond)
 	})
 	ctx := ollama.WithTrace(r.Context(), &ollama.Trace{
 		Update: func(l *ollama.Layer, n int64, err error) {
 			if n > 0 {
-				start() // flush initial state
+				// Block flushing progress updates until every
+				// layer is accounted for. Clients depend on a
+				// complete model size to calculate progress
+				// correctly; if they use an incomplete total,
+				// progress indicators would erratically jump
+				// as new layers are registered.
+				start()
 			}
 			mu.Lock()
-			progress[l] = n
+			progress[l] += n
 			mu.Unlock()
 		},
 	})
@@ -323,9 +330,9 @@ func (s *Local) handlePull(w http.ResponseWriter, r *http.Request) error {
 	for {
 		select {
 		case <-t.C:
-			pushUpdate()
+			flushProgress()
 		case err := <-done:
-			pushUpdate()
+			flushProgress()
 			if err != nil {
 				var status string
 				if errors.Is(err, ollama.ErrModelNotFound) {

server/model.go

@@ -82,7 +82,7 @@ func detectChatTemplate(layers []*layerGGML) ([]*layerGGML, error) {
 	for _, layer := range layers {
 		if s := layer.GGML.KV().ChatTemplate(); s != "" {
 			if t, err := template.Named(s); err != nil {
-				slog.Debug("template detection", "error", err)
+				slog.Debug("template detection", "error", err, "template", s)
 			} else {
 				layer, err := NewLayer(t.Reader(), "application/vnd.ollama.image.template")
 				if err != nil {

server/modelpath.go

@@ -31,9 +31,10 @@ const (
 
 var (
 	ErrInvalidImageFormat  = errors.New("invalid image format")
+	ErrInvalidDigestFormat = errors.New("invalid digest format")
 	ErrInvalidProtocol     = errors.New("invalid protocol scheme")
 	ErrInsecureProtocol    = errors.New("insecure protocol http")
-	ErrInvalidDigestFormat = errors.New("invalid digest format")
+	ErrModelPathInvalid    = errors.New("invalid model path")
 )
 
 func ParseModelPath(name string) ModelPath {
@@ -73,8 +74,6 @@ func ParseModelPath(name string) ModelPath {
 	return mp
 }
 
-var errModelPathInvalid = errors.New("invalid model path")
-
 func (mp ModelPath) GetNamespaceRepository() string {
 	return fmt.Sprintf("%s/%s", mp.Namespace, mp.Repository)
 }

server/prompt.go

@@ -26,7 +26,6 @@ func chatPrompt(ctx context.Context, m *Model, tokenize tokenizeFunc, opts *api.
 	var system []api.Message
 
 	isMllama := checkMllamaModelFamily(m)
-	isGemma3 := checkGemma3ModelFamily(m)
 
 	var imageNumTokens int
 	// TODO: Ideally we would compute this from the projector metadata but some pieces are implementation dependent
@@ -41,7 +40,7 @@ func chatPrompt(ctx context.Context, m *Model, tokenize tokenizeFunc, opts *api.
 	n := len(msgs) - 1
 	// in reverse, find all messages that fit into context window
 	for i := n; i >= 0; i-- {
-		if (isMllama || isGemma3) && len(msgs[i].Images) > 1 {
+		if isMllama && len(msgs[i].Images) > 1 {
 			return "", nil, errTooManyImages
 		}
 
@@ -158,12 +157,3 @@ func checkMllamaModelFamily(m *Model) bool {
 	}
 	return false
 }
-
-func checkGemma3ModelFamily(m *Model) bool {
-	for _, arch := range m.Config.ModelFamilies {
-		if arch == "gemma3" {
-			return true
-		}
-	}
-	return false
-}

server/routes.go

@@ -72,7 +72,7 @@ var (
 	errBadTemplate = errors.New("template error")
 )
 
-func modelOptions(model *Model, requestOpts map[string]interface{}) (api.Options, error) {
+func modelOptions(model *Model, requestOpts map[string]any) (api.Options, error) {
 	opts := api.DefaultOptions()
 	if err := opts.FromMap(model.Options); err != nil {
 		return api.Options{}, err
@@ -87,7 +87,7 @@ func modelOptions(model *Model, requestOpts map[string]interface{}) (api.Options
 
 // scheduleRunner schedules a runner after validating inputs such as capabilities and model options.
 // It returns the allocated runner, model instance, and consolidated options if successful and error otherwise.
-func (s *Server) scheduleRunner(ctx context.Context, name string, caps []Capability, requestOpts map[string]any, keepAlive *api.Duration) (llm.LlamaServer, *Model, *api.Options, error) {
+func (s *Server) scheduleRunner(ctx context.Context, name string, caps []model.Capability, requestOpts map[string]any, keepAlive *api.Duration) (llm.LlamaServer, *Model, *api.Options, error) {
 	if name == "" {
 		return nil, nil, nil, fmt.Errorf("model %w", errRequired)
 	}
@@ -144,7 +144,7 @@ func (s *Server) GenerateHandler(c *gin.Context) {
 		return
 	}
 
-	model, err := GetModel(name.String())
+	m, err := GetModel(name.String())
 	if err != nil {
 		switch {
 		case errors.Is(err, fs.ErrNotExist):
@@ -159,7 +159,7 @@ func (s *Server) GenerateHandler(c *gin.Context) {
 
 	// expire the runner
 	if req.Prompt == "" && req.KeepAlive != nil && int(req.KeepAlive.Seconds()) == 0 {
-		s.sched.expireRunner(model)
+		s.sched.expireRunner(m)
 
 		c.JSON(http.StatusOK, api.GenerateResponse{
 			Model:      req.Model,
@@ -176,9 +176,9 @@ func (s *Server) GenerateHandler(c *gin.Context) {
 		return
 	}
 
-	caps := []Capability{CapabilityCompletion}
+	caps := []model.Capability{model.CapabilityCompletion}
 	if req.Suffix != "" {
-		caps = append(caps, CapabilityInsert)
+		caps = append(caps, model.CapabilityInsert)
 	}
 
 	r, m, opts, err := s.scheduleRunner(c.Request.Context(), name.String(), caps, req.Options, req.KeepAlive)
@@ -203,7 +203,7 @@ func (s *Server) GenerateHandler(c *gin.Context) {
 		return
 	}
 
-	isMllama := checkMllamaModelFamily(model)
+	isMllama := checkMllamaModelFamily(m)
 	if isMllama && len(req.Images) > 1 {
 		c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": "this model only supports one image: more than one image sent"})
 		return
@@ -211,7 +211,7 @@ func (s *Server) GenerateHandler(c *gin.Context) {
 
 	images := make([]llm.ImageData, len(req.Images))
 	for i := range req.Images {
-		if isMllama && len(model.ProjectorPaths) > 0 {
+		if isMllama && len(m.ProjectorPaths) > 0 {
 			data, opts, err := mllama.Preprocess(bytes.NewReader(req.Images[i]))
 			if err != nil {
 				c.AbortWithStatusJSON(http.StatusInternalServerError, gin.H{"error": "error processing image"})
@@ -422,7 +422,7 @@ func (s *Server) EmbedHandler(c *gin.Context) {
 		return
 	}
 
-	r, m, opts, err := s.scheduleRunner(c.Request.Context(), name.String(), []Capability{}, req.Options, req.KeepAlive)
+	r, m, opts, err := s.scheduleRunner(c.Request.Context(), name.String(), []model.Capability{}, req.Options, req.KeepAlive)
 	if err != nil {
 		handleScheduleError(c, req.Model, err)
 		return
@@ -530,7 +530,7 @@ func (s *Server) EmbeddingsHandler(c *gin.Context) {
 		return
 	}
 
-	r, _, _, err := s.scheduleRunner(c.Request.Context(), name.String(), []Capability{}, req.Options, req.KeepAlive)
+	r, _, _, err := s.scheduleRunner(c.Request.Context(), name.String(), []model.Capability{}, req.Options, req.KeepAlive)
 	if err != nil {
 		handleScheduleError(c, req.Model, err)
 		return
@@ -777,7 +777,7 @@ func (s *Server) ShowHandler(c *gin.Context) {
 func GetModelInfo(req api.ShowRequest) (*api.ShowResponse, error) {
 	name := model.ParseName(req.Model)
 	if !name.IsValid() {
-		return nil, errModelPathInvalid
+		return nil, ErrModelPathInvalid
 	}
 	name, err := getExistingName(name)
 	if err != nil {
@@ -813,19 +813,20 @@ func GetModelInfo(req api.ShowRequest) (*api.ShowResponse, error) {
 	}
 
 	resp := &api.ShowResponse{
-		License:    strings.Join(m.License, "\n"),
-		System:     m.System,
-		Template:   m.Template.String(),
-		Details:    modelDetails,
-		Messages:   msgs,
-		ModifiedAt: manifest.fi.ModTime(),
+		License:      strings.Join(m.License, "\n"),
+		System:       m.System,
+		Template:     m.Template.String(),
+		Details:      modelDetails,
+		Messages:     msgs,
+		Capabilities: m.Capabilities(),
+		ModifiedAt:   manifest.fi.ModTime(),
 	}
 
 	var params []string
 	cs := 30
 	for k, v := range m.Options {
 		switch val := v.(type) {
-		case []interface{}:
+		case []any:
 			for _, nv := range val {
 				params = append(params, fmt.Sprintf("%-*s %#v", cs, k, nv))
 			}
@@ -1335,7 +1336,7 @@ func Serve(ln net.Listener) error {
 	return nil
 }
 
-func waitForStream(c *gin.Context, ch chan interface{}) {
+func waitForStream(c *gin.Context, ch chan any) {
 	c.Header("Content-Type", "application/json")
 	for resp := range ch {
 		switch r := resp.(type) {
@@ -1468,9 +1469,9 @@ func (s *Server) ChatHandler(c *gin.Context) {
 		return
 	}
 
-	caps := []Capability{CapabilityCompletion}
+	caps := []model.Capability{model.CapabilityCompletion}
 	if len(req.Tools) > 0 {
-		caps = append(caps, CapabilityTools)
+		caps = append(caps, model.CapabilityTools)
 	}
 
 	name := model.ParseName(req.Model)

server/sched.go

@@ -20,6 +20,7 @@ import (
 	"github.com/ollama/ollama/format"
 	"github.com/ollama/ollama/fs/ggml"
 	"github.com/ollama/ollama/llm"
+	"github.com/ollama/ollama/types/model"
 )
 
 type LlmRequest struct {
@@ -37,7 +38,7 @@ type Scheduler struct {
 	pendingReqCh  chan *LlmRequest
 	finishedReqCh chan *LlmRequest
 	expiredCh     chan *runnerRef
-	unloadedCh    chan interface{}
+	unloadedCh    chan any
 
 	loaded   map[string]*runnerRef
 	loadedMu sync.Mutex
@@ -67,7 +68,7 @@ func InitScheduler(ctx context.Context) *Scheduler {
 		pendingReqCh:  make(chan *LlmRequest, maxQueue),
 		finishedReqCh: make(chan *LlmRequest, maxQueue),
 		expiredCh:     make(chan *runnerRef, maxQueue),
-		unloadedCh:    make(chan interface{}, maxQueue),
+		unloadedCh:    make(chan any, maxQueue),
 		loaded:        make(map[string]*runnerRef),
 		newServerFn:   llm.NewLlamaServer,
 		getGpuFn:      discover.GetGPUInfo,
@@ -195,7 +196,7 @@ func (s *Scheduler) processPending(ctx context.Context) {
 					}
 
 					// Embedding models should always be loaded with parallel=1
-					if pending.model.CheckCapabilities(CapabilityCompletion) != nil {
+					if pending.model.CheckCapabilities(model.CapabilityCompletion) != nil {
 						numParallel = 1
 					}
 
@@ -617,8 +618,8 @@ func (runner *runnerRef) needsReload(ctx context.Context, req *LlmRequest) bool
 // a before and after GPU memory allocation.  The returned channel
 // will be notified when we're done waiting, or have timed out and should
 // proceed anyway
-func (runner *runnerRef) waitForVRAMRecovery() chan interface{} {
-	finished := make(chan interface{}, 1)
+func (runner *runnerRef) waitForVRAMRecovery() chan any {
+	finished := make(chan any, 1)
 
 	// CPU or Metal don't need checking, so no waiting required
 	// windows can page VRAM, only cuda currently can report accurate used vram usage
@@ -711,7 +712,7 @@ func pickBestFullFitByLibrary(req *LlmRequest, f *ggml.GGML, gpus discover.GpuIn
 			req.opts.NumCtx = req.origNumCtx * p
 			if !envconfig.SchedSpread() {
 				for _, g := range sgl {
-					if ok, estimatedVRAM = llm.PredictServerFit([]discover.GpuInfo{g}, f, req.model.AdapterPaths, req.model.ProjectorPaths, req.opts); ok {
+					if ok, estimatedVRAM = llm.PredictServerFit([]discover.GpuInfo{g}, f, req.model.AdapterPaths, req.model.ProjectorPaths, req.opts, p); ok {
 						slog.Info("new model will fit in available VRAM in single GPU, loading", "model", req.model.ModelPath, "gpu", g.ID, "parallel", p, "available", g.FreeMemory, "required", format.HumanBytes2(estimatedVRAM))
 						*numParallel = p
 						return []discover.GpuInfo{g}
@@ -727,7 +728,7 @@ func pickBestFullFitByLibrary(req *LlmRequest, f *ggml.GGML, gpus discover.GpuIn
 		// Now try all the GPUs
 		for _, p := range numParallelToTry {
 			req.opts.NumCtx = req.origNumCtx * p
-			if ok, estimatedVRAM = llm.PredictServerFit(sgl, f, req.model.AdapterPaths, req.model.ProjectorPaths, req.opts); ok {
+			if ok, estimatedVRAM = llm.PredictServerFit(sgl, f, req.model.AdapterPaths, req.model.ProjectorPaths, req.opts, p); ok {
 				slog.Info("new model will fit in available VRAM, loading", "model", req.model.ModelPath, "library", sgl[0].Library, "parallel", p, "required", format.HumanBytes2(estimatedVRAM))
 				*numParallel = p
 				return sgl
@@ -750,7 +751,7 @@ func pickBestPartialFitByLibrary(req *LlmRequest, f *ggml.GGML, gpus discover.Gp
 	var bestEstimate uint64
 	var bestFit int
 	for i, gl := range byLibrary {
-		_, estimatedVRAM := llm.PredictServerFit(gl, f, req.model.AdapterPaths, req.model.ProjectorPaths, req.opts)
+		_, estimatedVRAM := llm.PredictServerFit(gl, f, req.model.AdapterPaths, req.model.ProjectorPaths, req.opts, *numParallel)
 		if estimatedVRAM > bestEstimate {
 			bestEstimate = estimatedVRAM
 			bestFit = i
@@ -825,7 +826,7 @@ func (s *Scheduler) expireRunner(model *Model) {
 // If not, pick a runner to unload, else return nil and the request can be loaded
 func (s *Scheduler) maybeFindCPURunnerToUnload(req *LlmRequest, f *ggml.GGML, gpus discover.GpuInfoList) *runnerRef {
 	slog.Debug("evaluating if CPU model load will fit in available system memory")
-	estimate := llm.EstimateGPULayers(gpus, f, req.model.ProjectorPaths, req.opts)
+	estimate := llm.EstimateGPULayers(gpus, f, req.model.ProjectorPaths, req.opts, req.opts.NumCtx/req.origNumCtx)
 	if estimate.TotalSize <= gpus[0].FreeMemory {
 		slog.Debug("cpu inference mode, model fits in available system memory", "model", format.HumanBytes2(estimate.TotalSize), "available", format.HumanBytes2(gpus[0].FreeMemory))
 		return nil

template/gemma3-instruct.gotmpl

@@ -0,0 +1,13 @@
+{{- range $i, $_ := .Messages }}
+{{- $last := eq (len (slice $.Messages $i)) 1 }}
+{{- if eq .Role "user" }}<start_of_turn>user
+{{- if and (eq $i 1) $.System }}
+{{ $.System }}
+{{ end }}
+{{ .Content }}<end_of_turn>
+{{ else if eq .Role "assistant" }}<start_of_turn>model
+{{ .Content }}<end_of_turn>
+{{ end }}
+{{- if $last }}<start_of_turn>model
+{{ end }}
+{{- end }}

template/gemma3-instruct.json

@@ -0,0 +1,6 @@
+{
+  "stop": [
+    "<end_of_turn>"
+  ],
+  "temperature": 0.1
+}

template/index.json

@@ -87,6 +87,10 @@
     "template": "{{ bos_token }}{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role not supported') }}{% endif %}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if (message['role'] == 'assistant') %}{% set role = 'model' %}{% else %}{% set role = message['role'] %}{% endif %}{{ '<start_of_turn>' + role + '\n' + message['content'] | trim + '<end_of_turn>\n' }}{% endfor %}{% if add_generation_prompt %}{{'<start_of_turn>model\n'}}{% endif %}",
     "name": "gemma-instruct"
   },
+  {
+    "template": "{{ bos_token }}\n{%- if messages[0]['role'] == 'system' -%}\n    {%- if messages[0]['content'] is string -%}\n        {%- set first_user_prefix = messages[0]['content'] + '\n\n' -%}\n    {%- else -%}\n        {%- set first_user_prefix = messages[0]['content'][0]['text'] + '\n\n' -%}\n    {%- endif -%}\n    {%- set loop_messages = messages[1:] -%}\n{%- else -%}\n    {%- set first_user_prefix = \"\" -%}\n    {%- set loop_messages = messages -%}\n{%- endif -%}\n{%- for message in loop_messages -%}\n    {%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) -%}\n        {{ raise_exception(\"Conversation roles must alternate user/assistant/user/assistant/...\") }}\n    {%- endif -%}\n    {%- if (message['role'] == 'assistant') -%}\n        {%- set role = \"model\" -%}\n    {%- else -%}\n        {%- set role = message['role'] -%}\n    {%- endif -%}\n    {{ '<start_of_turn>' + role + '\n' + (first_user_prefix if loop.first else \"\") }}\n    {%- if message['content'] is string -%}\n        {{ message['content'] | trim }}\n    {%- elif message['content'] is iterable -%}\n        {%- for item in message['content'] -%}\n            {%- if item['type'] == 'image' -%}\n                {{ '<start_of_image>' }}\n            {%- elif item['type'] == 'text' -%}\n                {{ item['text'] | trim }}\n            {%- endif -%}\n        {%- endfor -%}\n    {%- else -%}\n        {{ raise_exception(\"Invalid content type\") }}\n    {%- endif -%}\n    {{ '<end_of_turn>\n' }}\n{%- endfor -%}\n{%- if add_generation_prompt -%}\n    {{'<start_of_turn>model\n'}}\n{%- endif -%}\n",
+    "name": "gemma3-instruct"
+  },
   {
     "template": "{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' %}{% if loop.index0 == 0 %}{% set content = bos_token + content %}{% endif %}{{ content }}{% endfor %}{% if add_generation_prompt %}{{ '<|start_header_id|>assistant<|end_header_id|>\n\n' }}{% endif %}",
     "name": "llama3-instruct"

template/testdata/gemma3-instruct.gotmpl/system-user-assistant-user

@@ -0,0 +1,10 @@
+<start_of_turn>user
+You are a helpful assistant.
+
+Hello, how are you?<end_of_turn>
+<start_of_turn>model
+I'm doing great. How can I help you today?<end_of_turn>
+<start_of_turn>user
+I'd like to show off how chat templating works!<end_of_turn>
+<start_of_turn>model
+

template/testdata/gemma3-instruct.gotmpl/user

@@ -0,0 +1,4 @@
+<start_of_turn>user
+Hello, how are you?<end_of_turn>
+<start_of_turn>model
+

template/testdata/gemma3-instruct.gotmpl/user-assistant-user

@@ -0,0 +1,8 @@
+<start_of_turn>user
+Hello, how are you?<end_of_turn>
+<start_of_turn>model
+I'm doing great. How can I help you today?<end_of_turn>
+<start_of_turn>user
+I'd like to show off how chat templating works!<end_of_turn>
+<start_of_turn>model
+

types/model/capability.go

@@ -0,0 +1,15 @@
+package model
+
+type Capability string
+
+const (
+	CapabilityCompletion = Capability("completion")
+	CapabilityTools      = Capability("tools")
+	CapabilityInsert     = Capability("insert")
+	CapabilityVision     = Capability("vision")
+	CapabilityEmbedding  = Capability("embedding")
+)
+
+func (c Capability) String() string {
+	return string(c)
+}