no parser yet

routes: fix built-in renderers for `api/generate`

convert/convert_gptoss.go

@@ -85,6 +85,19 @@ func (m *gptossModel) Tensors(ts []Tensor) []*ggml.Tensor {
 			case "scales":
 				mxfp4s[name].scales = t
 			}
+		} else if strings.HasSuffix(t.Name(), "gate_up_exps.bias") {
+			// gate_up_exps is interleaved, need to split into gate_exps and up_exps
+			// e.g. gate_exps, up_exps = gate_up_exps[:, 0::2, ...], gate_up_exps[:, 1::2, ...]
+			out = append(out, slices.Collect(splitDim(t, 1,
+				split{
+					Replacer: strings.NewReplacer("gate_up_exps", "gate_exps"),
+					slices:   []tensor.Slice{nil, tensor.S(0, int(t.Shape()[1]), 2)},
+				},
+				split{
+					Replacer: strings.NewReplacer("gate_up_exps", "up_exps"),
+					slices:   []tensor.Slice{nil, tensor.S(1, int(t.Shape()[1]), 2)},
+				},
+			))...)
 		} else {
 			out = append(out, &ggml.Tensor{
 				Name:     t.Name(),
@@ -97,17 +110,28 @@ func (m *gptossModel) Tensors(ts []Tensor) []*ggml.Tensor {
 
 	for name, mxfp4 := range mxfp4s {
 		dims := mxfp4.blocks.Shape()
-
-		if !strings.HasSuffix(name, ".weight") {
-			name += ".weight"
+		if strings.Contains(name, "ffn_down_exps") {
+			out = append(out, &ggml.Tensor{
+				Name:     name + ".weight",
+				Kind:     uint32(ggml.TensorTypeMXFP4),
+				Shape:    []uint64{dims[0], dims[1], dims[2] * dims[3] * 2},
+				WriterTo: mxfp4,
+			})
+		} else if strings.Contains(name, "ffn_gate_up_exps") {
+			// gate_up_exps is interleaved, need to split into gate_exps and up_exps
+			// e.g. gate_exps, up_exps = gate_up_exps[:, 0::2, ...], gate_up_exps[:, 1::2, ...]
+			out = append(out, &ggml.Tensor{
+				Name:     strings.Replace(name, "gate_up", "gate", 1) + ".weight",
+				Kind:     uint32(ggml.TensorTypeMXFP4),
+				Shape:    []uint64{dims[0], dims[1] / 2, dims[2] * dims[3] * 2},
+				WriterTo: mxfp4.slice(1, 0, int(dims[1]), 2),
+			}, &ggml.Tensor{
+				Name:     strings.Replace(name, "gate_up", "up", 1) + ".weight",
+				Kind:     uint32(ggml.TensorTypeMXFP4),
+				Shape:    []uint64{dims[0], dims[1] / 2, dims[2] * dims[3] * 2},
+				WriterTo: mxfp4.slice(1, 1, int(dims[1]), 2),
+			})
 		}
-
-		out = append(out, &ggml.Tensor{
-			Name:     name,
-			Kind:     uint32(ggml.TensorTypeMXFP4),
-			Shape:    []uint64{dims[0], dims[1], dims[2] * dims[3] * 2},
-			WriterTo: mxfp4,
-		})
 	}
 
 	return out
@@ -158,9 +182,21 @@ func (m *gptossModel) Replacements() []string {
 }
 
 type mxfp4 struct {
+	slices []tensor.Slice
+
 	blocks, scales Tensor
 }
 
+func (m *mxfp4) slice(dim, start, end, step int) *mxfp4 {
+	slice := slices.Repeat([]tensor.Slice{nil}, len(m.blocks.Shape()))
+	slice[dim] = tensor.S(start, end, step)
+	return &mxfp4{
+		slices: slice,
+		blocks: m.blocks,
+		scales: m.scales,
+	}
+}
+
 func (m *mxfp4) WriteTo(w io.Writer) (int64, error) {
 	var b bytes.Buffer
 	if _, err := m.blocks.WriteTo(&b); err != nil {
@@ -204,6 +240,13 @@ func (m *mxfp4) WriteTo(w io.Writer) (int64, error) {
 		return 0, err
 	}
 
+	if len(m.slices) > 0 {
+		out, err = out.Slice(m.slices...)
+		if err != nil {
+			return 0, err
+		}
+	}
+
 	out = tensor.Materialize(out)
 
 	if err := out.Reshape(out.Shape().TotalSize()); err != nil {

convert/tensor.go

@@ -16,7 +16,8 @@ import (
 
 type split struct {
 	*strings.Replacer
-	dim int
+	dim    int
+	slices []tensor.Slice
 
 	// fn is an optional function to apply to the tensor after slicing
 	fn func(tensor.Tensor) (tensor.Tensor, error)
@@ -32,9 +33,12 @@ func splitDim(t Tensor, dim int, splits ...split) iter.Seq[*ggml.Tensor] {
 			shape := slices.Clone(t.Shape())
 			shape[dim] = cmp.Or(uint64(split.dim), shape[dim]/uint64(len(splits)))
 
-			slice := slices.Repeat([]tensor.Slice{nil}, len(shape))
-			slice[dim] = tensor.S(offset, offset+int(shape[dim]))
-			offset += int(shape[dim])
+			slice := split.slices
+			if len(slice) == 0 {
+				slice = slices.Repeat([]tensor.Slice{nil}, len(shape))
+				slice[dim] = tensor.S(offset, offset+int(shape[dim]))
+				offset += int(shape[dim])
+			}
 
 			t.SetRepacker(func(_ string, data []float32, shape []uint64) ([]float32, error) {
 				dims := make([]int, len(shape))

discover/runner.go

@@ -408,7 +408,7 @@ func (r *bootstrapRunner) HasExited() bool {
 
 func bootstrapDevices(ctx context.Context, ollamaLibDirs []string, extraEnvs []string) []ml.DeviceInfo {
 	// TODO DRY out with llm/server.go
-	slog.Debug("spawing runner with", "OLLAMA_LIBRARY_PATH", ollamaLibDirs, "extra_envs", extraEnvs)
+	slog.Debug("spawning runner with", "OLLAMA_LIBRARY_PATH", ollamaLibDirs, "extra_envs", extraEnvs)
 	start := time.Now()
 	defer func() {
 		slog.Debug("bootstrap discovery took", "duration", time.Since(start), "OLLAMA_LIBRARY_PATH", ollamaLibDirs, "extra_envs", extraEnvs)

docs/gpu.md

@@ -51,11 +51,11 @@ sudo modprobe nvidia_uvm`
 Ollama supports the following AMD GPUs:
 
 ### Linux Support
-| Family         | Cards and accelerators                                                                                                                   |
-| -------------- | ---------------------------------------------------------------------------------------------------------------------------------------- |
-| AMD Radeon RX  | `7900 XTX` `7900 XT` `7900 GRE` `7800 XT` `7700 XT` `7600 XT` `7600` `6950 XT` `6900 XTX` `6900XT` `6800 XT` `6800` `Vega 64`            |
-| AMD Radeon PRO | `W7900` `W7800` `W7700` `W7600` `W7500` `W6900X` `W6800X Duo` `W6800X` `W6800` `V620` `V420` `V340` `V320` `Vega II Duo` `Vega II` `SSG` |
-| AMD Instinct   | `MI300X` `MI300A` `MI300` `MI250X` `MI250` `MI210` `MI200` `MI100` `MI60`                                                                |
+| Family         | Cards and accelerators                                                                                               |
+| -------------- | -------------------------------------------------------------------------------------------------------------------- |
+| AMD Radeon RX  | `7900 XTX` `7900 XT` `7900 GRE` `7800 XT` `7700 XT` `7600 XT` `7600` `6950 XT` `6900 XTX` `6900XT` `6800 XT` `6800`  |
+| AMD Radeon PRO | `W7900` `W7800` `W7700` `W7600` `W7500` `W6900X` `W6800X Duo` `W6800X` `W6800` `V620` `V420` `V340` `V320`           |
+| AMD Instinct   | `MI300X` `MI300A` `MI300` `MI250X` `MI250` `MI210` `MI200` `MI100`                                                   |
 
 ### Windows Support
 With ROCm v6.2, the following GPUs are supported on Windows.

fs/ggml/ggml.go

@@ -243,7 +243,6 @@ func (kv KV) OllamaEngineRequired() bool {
 		"gemma3",
 		"gemma3n",
 		"mistral3",
-		"qwen3",
 		"qwen3moe",
 		"llama4",
 		"mllama",

llama/patches/0026-GPU-discovery-enhancements.patch

@@ -13,13 +13,13 @@ management libraries for more accurate VRAM usage reporting if available.
  ggml/src/ggml-impl.h               |   8 +
  ggml/src/ggml-metal/ggml-metal.cpp |   3 +-
  ggml/src/mem_hip.cpp               | 449 +++++++++++++++++++++++++++++
- ggml/src/mem_nvml.cpp              | 172 +++++++++++
- 8 files changed, 718 insertions(+), 1 deletion(-)
+ ggml/src/mem_nvml.cpp              | 209 ++++++++++++++
+ 8 files changed, 755 insertions(+), 1 deletion(-)
  create mode 100644 ggml/src/mem_hip.cpp
  create mode 100644 ggml/src/mem_nvml.cpp
 
 diff --git a/ggml/include/ggml-backend.h b/ggml/include/ggml-backend.h
-index 0a2dae26..a6bf3378 100644
+index 0a2dae26a..a6bf33785 100644
 --- a/ggml/include/ggml-backend.h
 +++ b/ggml/include/ggml-backend.h
 @@ -169,6 +169,15 @@ extern "C" {
@@ -39,7 +39,7 @@ index 0a2dae26..a6bf3378 100644
  
      GGML_API const char *                  ggml_backend_dev_name(ggml_backend_dev_t device);
 diff --git a/ggml/src/CMakeLists.txt b/ggml/src/CMakeLists.txt
-index 33b3a15f..86191ef2 100644
+index 33b3a15f0..86191ef2c 100644
 --- a/ggml/src/CMakeLists.txt
 +++ b/ggml/src/CMakeLists.txt
 @@ -206,6 +206,8 @@ add_library(ggml-base
@@ -52,7 +52,7 @@ index 33b3a15f..86191ef2 100644
  
  target_include_directories(ggml-base PRIVATE .)
 diff --git a/ggml/src/ggml-cuda/ggml-cuda.cu b/ggml/src/ggml-cuda/ggml-cuda.cu
-index 531d6e27..3fa3a057 100644
+index 531d6e272..3fa3a0575 100644
 --- a/ggml/src/ggml-cuda/ggml-cuda.cu
 +++ b/ggml/src/ggml-cuda/ggml-cuda.cu
 @@ -261,6 +261,16 @@ static ggml_cuda_device_info ggml_cuda_init() {
@@ -184,7 +184,7 @@ index 531d6e27..3fa3a057 100644
                      /* .iface   = */ ggml_backend_cuda_device_interface,
                      /* .reg     = */ &reg,
 diff --git a/ggml/src/ggml-cuda/vendors/hip.h b/ggml/src/ggml-cuda/vendors/hip.h
-index 06f9e7c1..eb8f66cb 100644
+index 06f9e7c1e..eb8f66cb0 100644
 --- a/ggml/src/ggml-cuda/vendors/hip.h
 +++ b/ggml/src/ggml-cuda/vendors/hip.h
 @@ -5,6 +5,9 @@
@@ -206,7 +206,7 @@ index 06f9e7c1..eb8f66cb 100644
  #define cudaErrorPeerAccessAlreadyEnabled hipErrorPeerAccessAlreadyEnabled
  #define cudaErrorPeerAccessNotEnabled hipErrorPeerAccessNotEnabled
 diff --git a/ggml/src/ggml-impl.h b/ggml/src/ggml-impl.h
-index 86a1ebf6..9fc9fbfc 100644
+index 86a1ebf62..9fc9fbfcf 100644
 --- a/ggml/src/ggml-impl.h
 +++ b/ggml/src/ggml-impl.h
 @@ -635,6 +635,14 @@ static inline bool ggml_can_fuse(const struct ggml_cgraph * cgraph, int node_idx
@@ -225,7 +225,7 @@ index 86a1ebf6..9fc9fbfc 100644
  }
  #endif
 diff --git a/ggml/src/ggml-metal/ggml-metal.cpp b/ggml/src/ggml-metal/ggml-metal.cpp
-index 08ab4fc9..17999a61 100644
+index 08ab4fc91..17999a616 100644
 --- a/ggml/src/ggml-metal/ggml-metal.cpp
 +++ b/ggml/src/ggml-metal/ggml-metal.cpp
 @@ -535,6 +535,7 @@ static enum ggml_backend_dev_type ggml_backend_metal_device_get_type(ggml_backen
@@ -247,7 +247,7 @@ index 08ab4fc9..17999a61 100644
          /* .host_buffer           = */ false,
 diff --git a/ggml/src/mem_hip.cpp b/ggml/src/mem_hip.cpp
 new file mode 100644
-index 00000000..8ef19b8c
+index 000000000..8ef19b8cf
 --- /dev/null
 +++ b/ggml/src/mem_hip.cpp
 @@ -0,0 +1,449 @@
@@ -703,10 +703,10 @@ index 00000000..8ef19b8c
 \ No newline at end of file
 diff --git a/ggml/src/mem_nvml.cpp b/ggml/src/mem_nvml.cpp
 new file mode 100644
-index 00000000..aa05e9dc
+index 000000000..c9073cef0
 --- /dev/null
 +++ b/ggml/src/mem_nvml.cpp
-@@ -0,0 +1,172 @@
+@@ -0,0 +1,209 @@
 +// NVIDIA Management Library (NVML)
 +//
 +// https://developer.nvidia.com/management-library-nvml
@@ -721,6 +721,7 @@ index 00000000..aa05e9dc
 +#include "ggml-impl.h"
 +#include <filesystem>
 +#include <mutex>
++#include <array>
 +
 +#ifdef _WIN32
 +#    define WIN32_LEAN_AND_MEAN
@@ -787,6 +788,7 @@ index 00000000..aa05e9dc
 +  nvmlReturn_t (*nvmlShutdown)(void);
 +  nvmlReturn_t (*nvmlDeviceGetHandleByUUID)(const char *, nvmlDevice_t *);
 +  nvmlReturn_t (*nvmlDeviceGetMemoryInfo)(nvmlDevice_t, nvmlMemory_t *);
++  const char * (*nvmlErrorString)(nvmlReturn_t result);
 +} nvml { NULL, NULL, NULL, NULL, NULL };
 +static std::mutex ggml_nvml_lock;
 +
@@ -824,7 +826,8 @@ index 00000000..aa05e9dc
 +    nvml.nvmlShutdown = (nvmlReturn_enum (*)()) GetProcAddress((HMODULE)(nvml.handle), "nvmlShutdown");
 +    nvml.nvmlDeviceGetHandleByUUID = (nvmlReturn_t (*)(const char *, nvmlDevice_t *)) GetProcAddress((HMODULE)(nvml.handle), "nvmlDeviceGetHandleByUUID");
 +    nvml.nvmlDeviceGetMemoryInfo = (nvmlReturn_t (*)(nvmlDevice_t, nvmlMemory_t *)) GetProcAddress((HMODULE)(nvml.handle), "nvmlDeviceGetMemoryInfo");
-+    if (nvml.nvmlInit_v2 == NULL || nvml.nvmlShutdown == NULL || nvml.nvmlDeviceGetHandleByUUID == NULL || nvml.nvmlDeviceGetMemoryInfo == NULL) {
++    nvml.nvmlErrorString = (const char * (*)(nvmlReturn_enum)) GetProcAddress((HMODULE)(nvml.handle), "nvmlErrorString");
++    if (nvml.nvmlInit_v2 == NULL || nvml.nvmlShutdown == NULL || nvml.nvmlDeviceGetHandleByUUID == NULL || nvml.nvmlDeviceGetMemoryInfo == NULL || nvml.nvmlErrorString == NULL) {
 +        GGML_LOG_INFO("%s unable to locate required symbols in NVML.dll", __func__);
 +        FreeLibrary((HMODULE)(nvml.handle));
 +        nvml.handle = NULL;
@@ -833,11 +836,45 @@ index 00000000..aa05e9dc
 +
 +    SetErrorMode(old_mode);
 +
++    nvmlReturn_t status = nvml.nvmlInit_v2();
++    if (status != NVML_SUCCESS) {
++        GGML_LOG_INFO("%s unable to initialize NVML: %s\n", __func__, nvml.nvmlErrorString(status));
++        FreeLibrary((HMODULE)(nvml.handle));
++        nvml.handle = NULL;
++        return status;
++    }
 +#else
-+    // Not currently wired up on Linux
-+    return NVML_ERROR_NOT_SUPPORTED;
++    constexpr std::array<const char*, 2> libPaths = {
++        "/usr/lib/wsl/lib/libnvidia-ml.so.1", // Favor WSL2 path if present
++        "libnvidia-ml.so.1" // On a non-WSL2 system, it should be in the path
++    };
++    for (const char* path : libPaths) {
++        nvml.handle = dlopen(path, RTLD_LAZY);
++        if (nvml.handle) break;
++    }
++    if (nvml.handle == NULL) {
++        GGML_LOG_INFO("%s unable to load libnvidia-ml: %s\n", __func__, dlerror());
++        return NVML_ERROR_NOT_FOUND;
++    }
++    nvml.nvmlInit_v2 = (nvmlReturn_enum (*)()) dlsym(nvml.handle, "nvmlInit_v2");
++    nvml.nvmlShutdown = (nvmlReturn_enum (*)()) dlsym(nvml.handle, "nvmlShutdown");
++    nvml.nvmlDeviceGetHandleByUUID = (nvmlReturn_t (*)(const char *, nvmlDevice_t *)) dlsym(nvml.handle, "nvmlDeviceGetHandleByUUID");
++    nvml.nvmlDeviceGetMemoryInfo = (nvmlReturn_t (*)(nvmlDevice_t, nvmlMemory_t *)) dlsym(nvml.handle, "nvmlDeviceGetMemoryInfo");
++    nvml.nvmlErrorString = (const char * (*)(nvmlReturn_enum)) dlsym(nvml.handle, "nvmlErrorString");
++    if (nvml.nvmlInit_v2 == NULL || nvml.nvmlShutdown == NULL || nvml.nvmlDeviceGetHandleByUUID == NULL || nvml.nvmlDeviceGetMemoryInfo == NULL) {
++        GGML_LOG_INFO("%s unable to locate required symbols in libnvidia-ml.so", __func__);
++        dlclose(nvml.handle);
++        nvml.handle = NULL;
++        return NVML_ERROR_NOT_FOUND;
++    }
++    nvmlReturn_t status = nvml.nvmlInit_v2();
++    if (status != NVML_SUCCESS) {
++        GGML_LOG_INFO("%s unable to initialize NVML: %s\n", __func__, nvml.nvmlErrorString(status));
++        dlclose(nvml.handle);
++        nvml.handle = NULL;
++        return status;
++    }
 +#endif
-+    int status = nvml.nvmlInit_v2();
 +    return NVML_SUCCESS;
 +}
 +
@@ -849,14 +886,14 @@ index 00000000..aa05e9dc
 +    }
 +    nvmlReturn_enum status = nvml.nvmlShutdown();
 +    if (status != NVML_SUCCESS) {
-+        GGML_LOG_INFO("%s failed to shutdown NVML: %d\n", __func__, status);
++        GGML_LOG_INFO("%s failed to shutdown NVML: %s\n", __func__, nvml.nvmlErrorString(status));
 +    }
 +#ifdef _WIN32
 +    FreeLibrary((HMODULE)(nvml.handle));
-+    nvml.handle = NULL;
 +#else
-+    // Not currently wired up on Linux
++    dlclose(nvml.handle);
 +#endif
++    nvml.handle = NULL;
 +}
 +
 +int ggml_nvml_get_device_memory(const char *uuid, size_t *free, size_t *total) {

llm/server.go

@@ -1488,7 +1488,10 @@ func (s *llmServer) Completion(ctx context.Context, req CompletionRequest, fn fu
 	serverReq.Header.Set("Content-Type", "application/json")
 
 	res, err := http.DefaultClient.Do(serverReq)
-	if err != nil {
+	if err != nil && errors.Is(err, context.Canceled) {
+		// client closed connection
+		return err
+	} else if err != nil {
 		slog.Error("post predict", "error", err)
 		return errors.New("model runner has unexpectedly stopped, this may be due to resource limitations or an internal error, check ollama server logs for details")
 	}
@@ -1500,7 +1503,7 @@ func (s *llmServer) Completion(ctx context.Context, req CompletionRequest, fn fu
 			return fmt.Errorf("failed reading llm error response: %w", err)
 		}
 		log.Printf("llm predict error: %s", bodyBytes)
-		return api.StatusError{StatusCode: res.StatusCode, Status: res.Status, ErrorMessage: strings.TrimSpace(string(bodyBytes))}
+		return api.StatusError{StatusCode: res.StatusCode, ErrorMessage: strings.TrimSpace(string(bodyBytes))}
 	}
 
 	scanner := bufio.NewScanner(res.Body)

ml/backend/ggml/ggml/src/mem_nvml.cpp

@@ -12,6 +12,7 @@
 #include "ggml-impl.h"
 #include <filesystem>
 #include <mutex>
+#include <array>
 
 #ifdef _WIN32
 #    define WIN32_LEAN_AND_MEAN
@@ -78,6 +79,7 @@ struct {
   nvmlReturn_t (*nvmlShutdown)(void);
   nvmlReturn_t (*nvmlDeviceGetHandleByUUID)(const char *, nvmlDevice_t *);
   nvmlReturn_t (*nvmlDeviceGetMemoryInfo)(nvmlDevice_t, nvmlMemory_t *);
+  const char * (*nvmlErrorString)(nvmlReturn_t result);
 } nvml { NULL, NULL, NULL, NULL, NULL };
 static std::mutex ggml_nvml_lock;
 
@@ -115,7 +117,8 @@ int ggml_nvml_init() {
     nvml.nvmlShutdown = (nvmlReturn_enum (*)()) GetProcAddress((HMODULE)(nvml.handle), "nvmlShutdown");
     nvml.nvmlDeviceGetHandleByUUID = (nvmlReturn_t (*)(const char *, nvmlDevice_t *)) GetProcAddress((HMODULE)(nvml.handle), "nvmlDeviceGetHandleByUUID");
     nvml.nvmlDeviceGetMemoryInfo = (nvmlReturn_t (*)(nvmlDevice_t, nvmlMemory_t *)) GetProcAddress((HMODULE)(nvml.handle), "nvmlDeviceGetMemoryInfo");
-    if (nvml.nvmlInit_v2 == NULL || nvml.nvmlShutdown == NULL || nvml.nvmlDeviceGetHandleByUUID == NULL || nvml.nvmlDeviceGetMemoryInfo == NULL) {
+    nvml.nvmlErrorString = (const char * (*)(nvmlReturn_enum)) GetProcAddress((HMODULE)(nvml.handle), "nvmlErrorString");
+    if (nvml.nvmlInit_v2 == NULL || nvml.nvmlShutdown == NULL || nvml.nvmlDeviceGetHandleByUUID == NULL || nvml.nvmlDeviceGetMemoryInfo == NULL || nvml.nvmlErrorString == NULL) {
         GGML_LOG_INFO("%s unable to locate required symbols in NVML.dll", __func__);
         FreeLibrary((HMODULE)(nvml.handle));
         nvml.handle = NULL;
@@ -124,11 +127,45 @@ int ggml_nvml_init() {
 
     SetErrorMode(old_mode);
 
+    nvmlReturn_t status = nvml.nvmlInit_v2();
+    if (status != NVML_SUCCESS) {
+        GGML_LOG_INFO("%s unable to initialize NVML: %s\n", __func__, nvml.nvmlErrorString(status));
+        FreeLibrary((HMODULE)(nvml.handle));
+        nvml.handle = NULL;
+        return status;
+    }
 #else
-    // Not currently wired up on Linux
-    return NVML_ERROR_NOT_SUPPORTED;
+    constexpr std::array<const char*, 2> libPaths = {
+        "/usr/lib/wsl/lib/libnvidia-ml.so.1", // Favor WSL2 path if present
+        "libnvidia-ml.so.1" // On a non-WSL2 system, it should be in the path
+    };
+    for (const char* path : libPaths) {
+        nvml.handle = dlopen(path, RTLD_LAZY);
+        if (nvml.handle) break;
+    }
+    if (nvml.handle == NULL) {
+        GGML_LOG_INFO("%s unable to load libnvidia-ml: %s\n", __func__, dlerror());
+        return NVML_ERROR_NOT_FOUND;
+    }
+    nvml.nvmlInit_v2 = (nvmlReturn_enum (*)()) dlsym(nvml.handle, "nvmlInit_v2");
+    nvml.nvmlShutdown = (nvmlReturn_enum (*)()) dlsym(nvml.handle, "nvmlShutdown");
+    nvml.nvmlDeviceGetHandleByUUID = (nvmlReturn_t (*)(const char *, nvmlDevice_t *)) dlsym(nvml.handle, "nvmlDeviceGetHandleByUUID");
+    nvml.nvmlDeviceGetMemoryInfo = (nvmlReturn_t (*)(nvmlDevice_t, nvmlMemory_t *)) dlsym(nvml.handle, "nvmlDeviceGetMemoryInfo");
+    nvml.nvmlErrorString = (const char * (*)(nvmlReturn_enum)) dlsym(nvml.handle, "nvmlErrorString");
+    if (nvml.nvmlInit_v2 == NULL || nvml.nvmlShutdown == NULL || nvml.nvmlDeviceGetHandleByUUID == NULL || nvml.nvmlDeviceGetMemoryInfo == NULL) {
+        GGML_LOG_INFO("%s unable to locate required symbols in libnvidia-ml.so", __func__);
+        dlclose(nvml.handle);
+        nvml.handle = NULL;
+        return NVML_ERROR_NOT_FOUND;
+    }
+    nvmlReturn_t status = nvml.nvmlInit_v2();
+    if (status != NVML_SUCCESS) {
+        GGML_LOG_INFO("%s unable to initialize NVML: %s\n", __func__, nvml.nvmlErrorString(status));
+        dlclose(nvml.handle);
+        nvml.handle = NULL;
+        return status;
+    }
 #endif
-    int status = nvml.nvmlInit_v2();
     return NVML_SUCCESS;
 }
 
@@ -140,14 +177,14 @@ void ggml_nvml_release() {
     }
     nvmlReturn_enum status = nvml.nvmlShutdown();
     if (status != NVML_SUCCESS) {
-        GGML_LOG_INFO("%s failed to shutdown NVML: %d\n", __func__, status);
+        GGML_LOG_INFO("%s failed to shutdown NVML: %s\n", __func__, nvml.nvmlErrorString(status));
     }
 #ifdef _WIN32
     FreeLibrary((HMODULE)(nvml.handle));
-    nvml.handle = NULL;
 #else
-    // Not currently wired up on Linux
+    dlclose(nvml.handle);
 #endif
+    nvml.handle = NULL;
 }
 
 int ggml_nvml_get_device_memory(const char *uuid, size_t *free, size_t *total) {

model/bytepairencoding_test.go

@@ -251,7 +251,7 @@ func BenchmarkBytePairEncoding(b *testing.B) {
 		bts := bts[:n]
 		b.Run("encode"+strconv.Itoa(n), func(b *testing.B) {
 			b.ResetTimer()
-			for range b.N {
+			for b.Loop() {
 				_, err := tokenizer.Encode(string(bts), true)
 				if err != nil {
 					b.Fatal(err)
@@ -266,7 +266,7 @@ func BenchmarkBytePairEncoding(b *testing.B) {
 			}
 
 			b.ResetTimer()
-			for range b.N {
+			for b.Loop() {
 				_, err := tokenizer.Decode(ids)
 				if err != nil {
 					b.Fatal(err)
@@ -276,7 +276,7 @@ func BenchmarkBytePairEncoding(b *testing.B) {
 
 		b.Run("split"+strconv.Itoa(n), func(b *testing.B) {
 			b.ResetTimer()
-			for range b.N {
+			for b.Loop() {
 				slices.Collect(tokenizer.split(string(bts)))
 			}
 		})

model/models/llama4/process_image.go

@@ -73,7 +73,7 @@ func (p ImageProcessor) bestResolution(img image.Point, possibleResolutions []im
 	for i, res := range possibleResolutions {
 		scaleW := float64(res.X) / float64(w)
 		scaleH := float64(res.Y) / float64(h)
-		scale := math.Min(scaleW, scaleH)
+		scale := min(scaleW, scaleH)
 
 		scales[i] = scale
 	}
@@ -124,11 +124,11 @@ func (p ImageProcessor) maxResolution(imageRes, targetRes image.Point) image.Poi
 	if scaleW < scaleH {
 		newRes = image.Point{
 			targetRes.X,
-			int(math.Min(math.Floor(float64(imageRes.Y)*scaleW), float64(targetRes.Y))),
+			int(min(math.Floor(float64(imageRes.Y)*scaleW), float64(targetRes.Y))),
 		}
 	} else {
 		newRes = image.Point{
-			int(math.Min(math.Floor(float64(imageRes.X)*scaleH), float64(targetRes.X))),
+			int(min(math.Floor(float64(imageRes.X)*scaleH), float64(targetRes.X))),
 			targetRes.Y,
 		}
 	}

model/models/mllama/process_image.go

@@ -53,7 +53,7 @@ func (p ImageProcessor) fitToCanvas(imageSize, canvasSize image.Point) image.Poi
 	tw := min(max(imageSize.X, p.imageSize), canvasSize.X)
 	th := min(max(imageSize.Y, p.imageSize), canvasSize.Y)
 
-	r := math.Min(
+	r := min(
 		float64(tw)/float64(imageSize.X),
 		float64(th)/float64(imageSize.Y),
 	)
@@ -89,10 +89,10 @@ func (p ImageProcessor) optimalTiledCanvas(imageSize image.Point) image.Point {
 			if minUpscale == 0 {
 				minUpscale = s
 			} else {
-				minUpscale = math.Min(minUpscale, s)
+				minUpscale = min(minUpscale, s)
 			}
 		} else {
-			maxDownscale = math.Max(maxDownscale, s)
+			maxDownscale = max(maxDownscale, s)
 		}
 	}
 

model/parsers/glm46.go

@@ -0,0 +1,219 @@
+package parsers
+
+import (
+	"context"
+	"encoding/json"
+	"log/slog"
+	"strings"
+	"unicode"
+
+	"github.com/ollama/ollama/api"
+	"github.com/ollama/ollama/logutil"
+)
+
+const (
+	glm46CollectingContent glm46ParserState = iota
+	CollectingThinkingContent
+	CollectingToolContent
+)
+
+const (
+	thinkingCloseTag = "</think>"
+)
+
+// TODO(gguo): add a field for isThinking
+type GLM46Parser struct {
+	state  qwenParserState
+	buffer strings.Builder
+	tools  []api.Tool
+}
+
+func (p *GLM46Parser) HasToolSupport() bool {
+	return true
+}
+
+// TODO(gguo): changes this to reference an objects param
+func (p *GLM46Parser) HasThinkingSupport() bool {
+	return true
+}
+
+func (p *GLM46Parser) Init(tools []api.Tool, lastMessage *api.Message) []api.Tool {
+	p.tools = tools
+	// p.state = p.initialState()
+	return tools
+}
+
+type glm46EventThinkingContent struct {
+	content string
+}
+
+func (glm46EventThinkingContent) isGLM46Event() {}
+
+func (p *GLM46Parser) Add(s string, done bool) (content string, thinking string, calls []api.ToolCall, err error) {
+	p.buffer.WriteString(s)
+	events := p.parseEvents()
+
+	var toolCalls []api.ToolCall
+	var sb strings.Builder
+	for _, event := range events {
+		switch event := event.(type) {
+		case glm46EventRawToolCall:
+			toolCall, err := parseJSONToolCall(event, p.tools)
+			if err != nil {
+				slog.Warn("qwen tool call parsing failed", "error", err)
+				return "", "", nil, err
+			}
+			toolCalls = append(toolCalls, toolCall)
+		case glm46EventThinkingContent:
+			sb.WriteString(event.content)
+		case glm46EventContent:
+			// TODO(drifkin): if the same turn contains multiple interleaved content
+			// events, we naively append them together here.
+			sb.WriteString(event.content)
+		}
+	}
+
+	return sb.String(), "", toolCalls, nil
+}
+
+func (p *GLM46Parser) parseEvents() []glm46Event {
+	var all []glm46Event
+
+	keepLooping := true
+	for keepLooping {
+		var events []glm46Event
+		events, keepLooping = p.eat()
+		if len(events) > 0 {
+			all = append(all, events...)
+		}
+	}
+
+	if len(all) > 0 {
+		slog.Log(context.TODO(), logutil.LevelTrace, "qwen events parsed", "events", all, "state", p.state, "buffer", p.buffer.String())
+	}
+
+	return all
+}
+
+func emitContentBeforeTag(p *GLM46Parser, events []glm46Event, tag string) []glm46Event {
+	split := strings.SplitN(p.buffer.String(), tag, 2)
+	before := split[0]
+	before = strings.TrimRightFunc(before, unicode.IsSpace)
+	if len(before) > 0 {
+		events = append(events, glm46EventContent{content: before})
+	}
+	after := split[1]
+	p.buffer.Reset()
+	p.buffer.WriteString(after)
+	return events
+}
+
+func (p *GLM46Parser) eat() ([]glm46Event, bool) {
+	var events []glm46Event
+
+	switch p.state {
+	case glm46CollectingContent:
+		if strings.Contains(p.buffer.String(), toolOpenTag) {
+			events = emitContentBeforeTag(p, events, toolOpenTag)
+			p.state = glm46CollectingToolContent
+			return events, true
+		} else if overlapLen := overlap(p.buffer.String(), toolOpenTag); overlapLen > 0 {
+			beforePartialTag := p.buffer.String()[:len(p.buffer.String())-overlapLen]
+			trailingWhitespaceLen := trailingWhitespaceLen(beforePartialTag)
+			ambiguousStart := len(beforePartialTag) - trailingWhitespaceLen
+
+			unambiguous := p.buffer.String()[:ambiguousStart]
+			ambiguous := p.buffer.String()[ambiguousStart:]
+			p.buffer.Reset()
+			p.buffer.WriteString(ambiguous)
+			if len(unambiguous) > 0 { // why does qwen3coder not have this here
+				events = append(events, glm46EventContent{content: unambiguous})
+			}
+			return events, false
+		} else {
+			whitespaceLen := trailingWhitespaceLen(p.buffer.String())
+			ambiguousStart := len(p.buffer.String()) - whitespaceLen
+
+			unambiguous := p.buffer.String()[:ambiguousStart]
+			ambiguous := p.buffer.String()[ambiguousStart:]
+			p.buffer.Reset()
+			p.buffer.WriteString(ambiguous)
+			if len(unambiguous) > 0 {
+				events = append(events, glm46EventContent{content: unambiguous})
+			}
+			return events, false
+		}
+	case CollectingToolContent:
+		if strings.Contains(p.buffer.String(), glm46ToolCloseTag) {
+			split := strings.SplitN(p.buffer.String(), toolCloseTag, 2)
+			before := split[0]
+			if len(before) == 0 {
+				slog.Warn("qwen tool call closing tag found but no content before it")
+			}
+
+			after := strings.TrimLeftFunc(split[1], unicode.IsSpace)
+			events = append(events, glm46EventRawToolCall{raw: before})
+			p.buffer.Reset()
+			p.buffer.WriteString(after)
+			p.state = glm46CollectingContent
+			return events, true
+		} else {
+			return events, false
+		}
+	case glm46CollectingThinkingContent: // so we want to hip the unambiguous stuff
+		if strings.Contains(p.buffer.String(), thinkingCloseTag) {
+			split := strings.SplitN(p.buffer.String(), thinkingCloseTag, 2)
+			before := split[0]
+			if len(before) == 0 {
+				slog.Warn("qwen tool call closing tag found but no content before it")
+			}
+			after := strings.TrimLeftFunc(split[1], unicode.IsSpace)
+			if len(before) > 0 {
+				events = append(events, glm46EventThinkingContent{content: before})
+			}
+			p.buffer.Reset()
+			p.buffer.WriteString(after)
+			p.state = glm46CollectingContent
+			return events, true
+		} else if overlapLen := overlap(p.buffer.String(), thinkingCloseTag); overlapLen > 0 { // we see part of a close thinking tag
+			beforePartialTag := p.buffer.String()[:len(p.buffer.String())-overlapLen]
+			trailingWhitespaceLen := trailingWhitespaceLen(beforePartialTag)
+			ambiguousStart := len(beforePartialTag) - trailingWhitespaceLen
+
+			unambiguous := p.buffer.String()[:ambiguousStart]
+			ambiguous := p.buffer.String()[ambiguousStart:]
+			p.buffer.Reset()
+			p.buffer.WriteString(ambiguous)
+			if len(unambiguous) > 0 {
+				events = append(events, glm46EventThinkingContent{content: unambiguous})
+			}
+			return events, false
+		} else {
+			whitespaceLen := trailingWhitespaceLen(p.buffer.String())
+			ambiguousStart := len(p.buffer.String()) - whitespaceLen
+
+			unambiguous := p.buffer.String()[:ambiguousStart]
+			ambiguous := p.buffer.String()[ambiguousStart:]
+			p.buffer.Reset()
+			p.buffer.WriteString(ambiguous)
+			if len(unambiguous) > 0 {
+				events = append(events, glm46EventThinkingContent{content: unambiguous})
+			}
+			return events, false
+		}
+	default:
+		panic("unreachable")
+	}
+}
+
+func parseJSONToolCall(raw glm46EventRawToolCall, tools []api.Tool) (api.ToolCall, error) {
+	var toolCallFunction api.ToolCallFunction
+	if err := json.Unmarshal([]byte(raw.raw), &toolCallFunction); err != nil {
+		return api.ToolCall{}, err
+	}
+
+	toolCall := api.ToolCall{}
+	toolCall.Function = toolCallFunction
+
+	return toolCall, nil
+}

model/parsers/parsers.go

@@ -21,6 +21,9 @@ func ParserForName(name string) Parser {
 	case "qwen3-coder":
 		parser := &Qwen3CoderParser{}
 		return parser
+	case "glm-4.6":
+		parser := &GLM46Parser{}
+		return parser
 	case "passthrough":
 		return &PassthroughParser{}
 	case "harmony":

model/renderers/glm46_test.go

@@ -0,0 +1,239 @@
+package renderers
+
+import (
+	"testing"
+
+	"github.com/google/go-cmp/cmp"
+	"github.com/ollama/ollama/api"
+)
+
+func TestGLM46Renderer(t *testing.T) {
+	tests := []struct {
+		name       string
+		messages   []api.Message
+		tools      []api.Tool
+		thinkValue *api.ThinkValue
+		expected   string
+	}{
+		{
+			name: "basic",
+			messages: []api.Message{
+				{Role: "user", Content: "Hello, how are you?"},
+			},
+			expected: `[gMASK]<sop><|user|>
+Hello, how are you?<|assistant|>`,
+		},
+		{
+			name: "basic with system message",
+			messages: []api.Message{
+				{Role: "system", Content: "You are a helpful assistant."},
+				{Role: "user", Content: "Hello, how are you?"},
+			},
+			expected: `[gMASK]<sop><|system|>
+You are a helpful assistant.<|user|>
+Hello, how are you?<|assistant|>`,
+		},
+		{
+			name: "basic with user assistant user",
+			messages: []api.Message{
+				{Role: "user", Content: "What is the capital of France?"},
+				{Role: "assistant", Thinking: "Let me analyze the request...", Content: "The capital of France is Paris."},
+				{Role: "user", Content: "Fantastic!"},
+			},
+			expected: `[gMASK]<sop><|user|>
+What is the capital of France?<|assistant|>
+The capital of France is Paris.<|user|>
+Fantastic!<|assistant|>`,
+		},
+		{
+			name: "tools",
+			messages: []api.Message{
+				{Role: "system", Content: "You are a helpful assistant with access to tools."},
+				{Role: "user", Content: "What is the weather like in Tokyo?"},
+			},
+			tools: []api.Tool{
+				{
+					Type: "function",
+					Function: api.ToolFunction{
+						Name:        "get_weather",
+						Description: "Get the current weather in a given location",
+						Parameters: api.ToolFunctionParameters{
+							Type:     "object",
+							Required: []string{"location"},
+							Properties: map[string]api.ToolProperty{
+								"location": {
+									Type:        api.PropertyType{"string"},
+									Description: "The city and state, e.g. San Francisco, CA",
+								},
+								"unit": {
+									Type: api.PropertyType{"string"},
+									Enum: []any{"celsius", "fahrenheit"},
+								},
+							},
+						},
+					},
+				},
+			},
+			expected: `[gMASK]<sop><|system|>
+# Tools
+
+You may call one or more functions to assist with the user query.
+
+You are provided with function signatures within <tools></tools> XML tags:
+<tools>
+{"type":"function","function":{"name":"get_weather","description":"Get the current weather in a given location","parameters":{"type":"object","required":["location"],"properties":{"location":{"type":"string","description":"The city and state, e.g. San Francisco, CA"},"unit":{"type":"string","description":"","enum":["celsius","fahrenheit"]}}}}}
+</tools>
+
+For each function call, output the function name and arguments within the following XML format:
+<tool_call>{function-name}
+<arg_key>{arg-key-1}</arg_key>
+<arg_value>{arg-value-1}</arg_value>
+<arg_key>{arg-key-2}</arg_key>
+<arg_value>{arg-value-2}</arg_value>
+...
+</tool_call><|system|>
+You are a helpful assistant with access to tools.<|user|>
+What is the weather like in Tokyo?<|assistant|>`,
+		},
+		{
+			name: "tool calls",
+			messages: []api.Message{
+				{Role: "system", Content: "You are a helpful assistant with access to tools."},
+				{Role: "user", Content: "What is the weather like in Tokyo?"},
+				{
+					Role: "assistant",
+					ToolCalls: []api.ToolCall{
+						{
+							Function: api.ToolCallFunction{
+								Name: "get_weather",
+								Arguments: api.ToolCallFunctionArguments{
+									"location": "Tokyo, Japan",
+									"unit":     "celsius",
+								},
+							},
+						},
+						{
+							Function: api.ToolCallFunction{
+								Name: "get_weather",
+								Arguments: api.ToolCallFunctionArguments{
+									"location": "Japan",
+									"unit":     "fahrenheit",
+								},
+							},
+						},
+					},
+				},
+				{
+					Role:     "tool",
+					Content:  "{\"temperature\": 22, \"weather\": \"partly cloudy\", \"humidity\": 65}",
+					ToolName: "get_weather",
+				},
+				{
+					Role:     "tool",
+					Content:  "{\"temperature\": 68, \"weather\": \"sunny\", \"humidity\": 75}",
+					ToolName: "get_weather",
+				},
+				{
+					Role:    "assistant",
+					Content: "The weather in Tokyo is currently partly cloudy with a temperature of 22°C and 65% humidity. It's a pleasant day with moderate temperatures.",
+				},
+			},
+			tools: []api.Tool{
+				{
+					Type: "function",
+					Function: api.ToolFunction{
+						Name:        "get_weather",
+						Description: "Get the current weather in a given location",
+						Parameters: api.ToolFunctionParameters{
+							Type:     "object",
+							Required: []string{"location"},
+							Properties: map[string]api.ToolProperty{
+								"location": {
+									Type:        api.PropertyType{"string"},
+									Description: "The city and state, e.g. San Francisco, CA",
+								},
+								"unit": {
+									Type: api.PropertyType{"string"},
+									Enum: []any{"celsius", "fahrenheit"},
+								},
+							},
+						},
+					},
+				},
+			},
+			expected: `[gMASK]<sop><|system|>
+# Tools
+
+You may call one or more functions to assist with the user query.
+
+You are provided with function signatures within <tools></tools> XML tags:
+<tools>
+{"type":"function","function":{"name":"get_weather","description":"Get the current weather in a given location","parameters":{"type":"object","required":["location"],"properties":{"location":{"type":"string","description":"The city and state, e.g. San Francisco, CA"},"unit":{"type":"string","description":"","enum":["celsius","fahrenheit"]}}}}}
+</tools>
+
+For each function call, output the function name and arguments within the following XML format:
+<tool_call>{function-name}
+<arg_key>{arg-key-1}</arg_key>
+<arg_value>{arg-value-1}</arg_value>
+<arg_key>{arg-key-2}</arg_key>
+<arg_value>{arg-value-2}</arg_value>
+...
+</tool_call><|system|>
+You are a helpful assistant with access to tools.<|user|>
+What is the weather like in Tokyo?<|assistant|>
+<think></think>
+<tool_call>get_weather
+<arg_key>location</arg_key>
+<arg_value>Tokyo, Japan</arg_value>
+<arg_key>unit</arg_key>
+<arg_value>celsius</arg_value>
+</tool_call>
+<tool_call>get_weather
+<arg_key>location</arg_key>
+<arg_value>Japan</arg_value>
+<arg_key>unit</arg_key>
+<arg_value>fahrenheit</arg_value>
+</tool_call><|observation|>
+<tool_response>
+{"temperature": 22, "weather": "partly cloudy", "humidity": 65}
+</tool_response>
+<tool_response>
+{"temperature": 68, "weather": "sunny", "humidity": 75}
+</tool_response><|assistant|>
+<think></think>
+The weather in Tokyo is currently partly cloudy with a temperature of 22°C and 65% humidity. It's a pleasant day with moderate temperatures.<|assistant|>`,
+		},
+		{
+			name: "think true",
+			messages: []api.Message{
+				{Role: "user", Content: "Hello, how are you?"},
+			},
+			thinkValue: &api.ThinkValue{Value: true},
+			expected: `[gMASK]<sop><|user|>
+Hello, how are you?<|assistant|>`,
+		},
+		{
+			name: "think false",
+			messages: []api.Message{
+				{Role: "user", Content: "Hello, how are you?"},
+			},
+			thinkValue: &api.ThinkValue{Value: false},
+			expected: `[gMASK]<sop><|user|>
+Hello, how are you?/nothink<|assistant|>
+<think></think>`,
+		},
+	}
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			rendered, err := GLM46Renderer(tt.messages, tt.tools, tt.thinkValue)
+			if err != nil {
+				t.Fatal(err)
+			}
+			if diff := cmp.Diff(rendered, tt.expected); diff != "" {
+				t.Errorf("mismatch (-got +want):\n%s", diff)
+				t.Logf("Got:\n%s", rendered)
+				t.Logf("Expected:\n%s", tt.expected)
+			}
+		})
+	}
+}

model/renderers/gml46.go

@@ -0,0 +1,109 @@
+package renderers
+
+import (
+	"encoding/json"
+	"fmt"
+	"strings"
+
+	"github.com/ollama/ollama/api"
+)
+
+func GLM46Renderer(messages []api.Message, tools []api.Tool, thinkValue *api.ThinkValue) (string, error) {
+	var sb strings.Builder
+
+	sb.WriteString("[gMASK]<sop>")
+
+	var lastUserIndex int
+	for i, message := range messages {
+		if message.Role == "user" {
+			lastUserIndex = i
+		}
+	}
+
+	if len(tools) > 0 {
+		sb.WriteString("<|system|>\n")
+		sb.WriteString("# Tools\n\n")
+		sb.WriteString("You may call one or more functions to assist with the user query.\n\n")
+		sb.WriteString("You are provided with function signatures within <tools></tools> XML tags:\n")
+		sb.WriteString("<tools>\n")
+		for _, tool := range tools {
+			d, _ := json.Marshal(tool)
+			sb.WriteString(string(d) + "\n")
+		}
+		sb.WriteString("</tools>\n\n")
+		sb.WriteString("For each function call, output the function name and arguments within the following XML format:\n")
+		sb.WriteString("<tool_call>{function-name}\n")
+		sb.WriteString("<arg_key>{arg-key-1}</arg_key>\n")
+		sb.WriteString("<arg_value>{arg-value-1}</arg_value>\n")
+		sb.WriteString("<arg_key>{arg-key-2}</arg_key>\n")
+		sb.WriteString("<arg_value>{arg-value-2}</arg_value>\n")
+		sb.WriteString("...\n")
+		sb.WriteString("</tool_call>")
+	}
+
+	for i, message := range messages {
+		switch message.Role {
+		case "user":
+			sb.WriteString("<|user|>\n")
+			sb.WriteString(message.Content)
+			if thinkValue != nil && !thinkValue.Bool() && !strings.HasSuffix(message.Content, "/nothink") {
+				sb.WriteString("/nothink")
+			}
+		case "assistant":
+			sb.WriteString("<|assistant|>")
+			if i > lastUserIndex {
+				if message.Thinking != "" {
+					sb.WriteString("\n<think>" + message.Thinking + "</think>")
+				} else {
+					sb.WriteString("\n<think></think>")
+				}
+			}
+			if message.Content != "" {
+				sb.WriteString("\n" + message.Content)
+			}
+			if len(message.ToolCalls) > 0 {
+				for _, toolCall := range message.ToolCalls {
+					sb.WriteString("\n<tool_call>" + toolCall.Function.Name + "\n")
+					for key, value := range toolCall.Function.Arguments {
+						sb.WriteString("<arg_key>" + key + "</arg_key>\n")
+
+						var valueStr string
+						if str, ok := value.(string); ok {
+							valueStr = str
+						} else {
+							jsonBytes, err := json.Marshal(value)
+							if err != nil {
+								valueStr = fmt.Sprintf("%v", value)
+							} else {
+								valueStr = string(jsonBytes)
+							}
+						}
+
+						sb.WriteString("<arg_value>" + valueStr + "</arg_value>\n")
+					}
+
+					sb.WriteString("</tool_call>")
+				}
+			}
+		case "tool":
+			if i == 0 || messages[i-1].Role != "tool" {
+				sb.WriteString("<|observation|>")
+			}
+			sb.WriteString("\n<tool_response>\n")
+			sb.WriteString(message.Content)
+			sb.WriteString("\n</tool_response>")
+		case "system":
+			sb.WriteString("<|system|>\n")
+			sb.WriteString(message.Content)
+		}
+	}
+
+	// Add generation prompt
+	sb.WriteString("<|assistant|>")
+	fmt.Println("thinkValue", thinkValue, thinkValue.Bool())
+	if thinkValue != nil && !thinkValue.Bool() {
+		sb.WriteString("\n<think></think>")
+	}
+
+	return sb.String(), nil
+}

model/renderers/renderer.go

@@ -20,6 +20,8 @@ func rendererForName(name string) rendererFunc {
 	switch name {
 	case "qwen3-coder":
 		return Qwen3CoderRenderer
+	case "glm-4.6":
+		return GLM46Renderer
 	default:
 		return nil
 	}

openai/openai.go

@@ -567,18 +567,24 @@ func FromChatRequest(r ChatCompletionRequest) (*api.ChatRequest, error) {
 	}
 
 	var think *api.ThinkValue
+	var effort string
+
 	if r.Reasoning != nil {
-		if !slices.Contains([]string{"high", "medium", "low", "none"}, r.Reasoning.Effort) {
-			return nil, fmt.Errorf("invalid reasoning value: '%s' (must be \"high\", \"medium\", \"low\", or \"none\")", r.Reasoning.Effort)
+		effort = r.Reasoning.Effort
+	} else if r.ReasoningEffort != nil {
+		effort = *r.ReasoningEffort
+	}
+
+	if effort != "" {
+		if !slices.Contains([]string{"high", "medium", "low", "none"}, effort) {
+			return nil, fmt.Errorf("invalid reasoning value: '%s' (must be \"high\", \"medium\", \"low\", or \"none\")", effort)
 		}
 
-		if r.Reasoning.Effort == "none" {
+		if effort == "none" {
 			think = &api.ThinkValue{Value: false}
 		} else {
-			think = &api.ThinkValue{Value: r.Reasoning.Effort}
+			think = &api.ThinkValue{Value: effort}
 		}
-	} else if r.ReasoningEffort != nil {
-		think = &api.ThinkValue{Value: *r.ReasoningEffort}
 	}
 
 	return &api.ChatRequest{

runner/llamarunner/runner.go

@@ -85,10 +85,10 @@ type Sequence struct {
 	doneReason llm.DoneReason
 
 	// Metrics
-	startProcessingTime time.Time
-	startGenerationTime time.Time
-	numDecoded          int
-	numPromptInputs     int
+	processingDuration time.Duration
+	generationDuration time.Duration
+	numDecoded         int
+	numPromptInputs    int
 }
 
 type NewSequenceParams struct {
@@ -106,8 +106,6 @@ var errorInputTooLong = errors.New("the input length exceeds the context length"
 func (s *Server) NewSequence(prompt string, images []llm.ImageData, params NewSequenceParams) (*Sequence, error) {
 	s.ready.Wait()
 
-	startTime := time.Now()
-
 	inputs, err := s.inputs(prompt, images)
 	if err != nil {
 		return nil, fmt.Errorf("failed to process inputs: %w", err)
@@ -153,18 +151,17 @@ func (s *Server) NewSequence(prompt string, images []llm.ImageData, params NewSe
 	}
 
 	return &Sequence{
-		inputs:              inputs,
-		numPromptInputs:     len(inputs),
-		startProcessingTime: startTime,
-		numPredict:          params.numPredict,
-		pendingResponses:    make([]string, 0),
-		responses:           make(chan string, 100),
-		quit:                make(chan bool, 1),
-		embedding:           make(chan []float32, 1),
-		samplingCtx:         sc,
-		embeddingOnly:       params.embedding,
-		stop:                params.stop,
-		numKeep:             params.numKeep,
+		inputs:           inputs,
+		numPromptInputs:  len(inputs),
+		numPredict:       params.numPredict,
+		pendingResponses: make([]string, 0),
+		responses:        make(chan string, 100),
+		quit:             make(chan bool, 1),
+		embedding:        make(chan []float32, 1),
+		samplingCtx:      sc,
+		embeddingOnly:    params.embedding,
+		stop:             params.stop,
+		numKeep:          params.numKeep,
 	}, nil
 }
 
@@ -454,8 +451,8 @@ func (s *Server) processBatch(tokenBatch *llama.Batch, embedBatch *llama.Batch)
 		return nil
 	}
 
-	err := s.lc.Decode(batch)
-	if err != nil {
+	t := time.Now()
+	if err := s.lc.Decode(batch); err != nil {
 		return fmt.Errorf("failed to decode batch: %w", err)
 	}
 
@@ -475,9 +472,12 @@ func (s *Server) processBatch(tokenBatch *llama.Batch, embedBatch *llama.Batch)
 			continue
 		}
 
-		seq.numDecoded += 1
-		if seq.numDecoded == 1 {
-			seq.startGenerationTime = time.Now()
+		s.lc.Synchronize()
+		seq.numDecoded++
+		if seq.numDecoded > 1 {
+			seq.generationDuration += time.Since(t)
+		} else {
+			seq.processingDuration += time.Since(t)
 		}
 
 		// if done processing the prompt, generate an embedding and return
@@ -668,9 +668,9 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 					Done:               true,
 					DoneReason:         seq.doneReason,
 					PromptEvalCount:    seq.numPromptInputs,
-					PromptEvalDuration: seq.startGenerationTime.Sub(seq.startProcessingTime),
+					PromptEvalDuration: seq.processingDuration,
 					EvalCount:          seq.numDecoded,
-					EvalDuration:       time.Since(seq.startGenerationTime),
+					EvalDuration:       seq.generationDuration,
 				}); err != nil {
 					http.Error(w, fmt.Sprintf("failed to encode final response: %v", err), http.StatusInternalServerError)
 				}

runner/ollamarunner/runner.go

@@ -94,10 +94,11 @@ type Sequence struct {
 	doneReason llm.DoneReason
 
 	// Metrics
-	startProcessingTime time.Time
-	startGenerationTime time.Time
-	numPredicted        int
-	numPromptInputs     int
+	startedAt, lastUpdatedAt time.Time
+	processingDuration       time.Duration
+	samplingDuration         time.Duration
+	numPredicted             int
+	numPromptInputs          int
 }
 
 type NewSequenceParams struct {
@@ -115,8 +116,6 @@ var errorInputTooLong = errors.New("the input length exceeds the context length"
 func (s *Server) NewSequence(prompt string, images []llm.ImageData, params NewSequenceParams) (*Sequence, error) {
 	s.ready.Wait()
 
-	startTime := time.Now()
-
 	inputs, ctxs, mmStore, err := s.inputs(prompt, images)
 	if err != nil {
 		return nil, fmt.Errorf("failed to process inputs: %w", err)
@@ -176,21 +175,20 @@ func (s *Server) NewSequence(prompt string, images []llm.ImageData, params NewSe
 	// TODO(jessegross): Ingest cached history for grammar
 
 	return &Sequence{
-		ctxs:                ctxs,
-		mmStore:             mmStore,
-		inputs:              inputs,
-		numPromptInputs:     len(inputs),
-		startProcessingTime: startTime,
-		numPredict:          params.numPredict,
-		pendingResponses:    make([]string, 0),
-		responses:           make(chan string, 100),
-		quit:                make(chan bool, 1),
-		embedding:           make(chan []float32, 1),
-		sampler:             params.sampler,
-		embeddingOnly:       params.embedding,
-		stop:                params.stop,
-		numKeep:             params.numKeep,
-		shift:               params.shift,
+		ctxs:             ctxs,
+		mmStore:          mmStore,
+		inputs:           inputs,
+		numPromptInputs:  len(inputs),
+		numPredict:       params.numPredict,
+		pendingResponses: make([]string, 0),
+		responses:        make(chan string, 100),
+		quit:             make(chan bool, 1),
+		embedding:        make(chan []float32, 1),
+		sampler:          params.sampler,
+		embeddingOnly:    params.embedding,
+		stop:             params.stop,
+		numKeep:          params.numKeep,
+		shift:            params.shift,
 	}, nil
 }
 
@@ -336,9 +334,6 @@ type Server struct {
 	// TODO (jmorganca): make this n_batch
 	batchSize int
 
-	// Used to signal a hard failure during async processing which will panic the runner
-	hardErrCh chan error
-
 	// Simple counter used only for trace logging batches
 	batchID int
 
@@ -421,25 +416,25 @@ func (s *Server) run(ctx context.Context) {
 
 	supportsAsync := pooling.Type(s.model.Backend().Config().Uint("pooling_type")) == pooling.TypeNone
 
-	var activeBatch batchState
+	var previousBatch batchState
 	for {
 		select {
 		case <-ctx.Done():
 			return
-		case err := <-s.hardErrCh:
-			panic(err)
 		default:
 			var err error
-			activeBatch, err = s.forwardBatch(activeBatch)
+			nextBatch, err := s.forwardBatch(previousBatch)
 			if err != nil {
 				panic(err)
 			}
 
 			if supportsAsync {
-				go s.computeBatch(activeBatch)
+				go s.computeBatch(nextBatch)
 			} else {
-				s.computeBatch(activeBatch)
+				s.computeBatch(nextBatch)
 			}
+
+			previousBatch = nextBatch
 		}
 	}
 }
@@ -581,6 +576,13 @@ func (s *Server) forwardBatch(pendingBatch batchState) (nextBatch batchState, er
 		seq.inputs = seq.inputs[len(seq.pendingInputs):]
 	}
 
+	startedAt := time.Now()
+	for i := range nextBatch.seqs {
+		if nextBatch.seqs[i] != nil && nextBatch.seqs[i].startedAt.IsZero() {
+			nextBatch.seqs[i].startedAt = startedAt
+		}
+	}
+
 	if resumeSeq != -1 {
 		s.nextSeq = resumeSeq
 	} else {
@@ -675,9 +677,7 @@ func (s *Server) computeBatch(activeBatch batchState) {
 		// don't sample prompt processing
 		if len(seq.inputs) != 0 {
 			if !s.cache.enabled {
-				s.hardErrCh <- fmt.Errorf("caching disabled but unable to fit entire input in a batch")
-				s.mu.Unlock()
-				return
+				panic("caching disabled but unable to fit entire input in a batch")
 			}
 			continue
 		}
@@ -701,6 +701,7 @@ func (s *Server) computeBatch(activeBatch batchState) {
 		activeBatch.modelOutput)
 
 	outputs := activeBatch.modelOutput.Floats()
+	t := time.Now()
 
 	logutil.Trace("computeBatch: logits ready", "batchID", activeBatch.id)
 
@@ -713,8 +714,10 @@ func (s *Server) computeBatch(activeBatch batchState) {
 			continue
 		}
 
+		seq.lastUpdatedAt = t
 		if seq.numPredicted == 1 {
-			seq.startGenerationTime = time.Now()
+			seq.processingDuration = seq.lastUpdatedAt.Sub(seq.startedAt)
+			seq.startedAt = seq.lastUpdatedAt
 		}
 
 		// if done processing the prompt, generate an embedding and return
@@ -729,8 +732,7 @@ func (s *Server) computeBatch(activeBatch batchState) {
 		logutil.Trace("computeBatch: vocab details", "batchID", activeBatch.id, "seqIdx", i, "len(logits)", len(outputs), "len(activeBatch.batch.Outputs)", activeBatch.batch.Outputs.Dim(0), "vocabSize", vocabSize, "iBatches", iBatches)
 		token, err := seq.sampler.Sample(outputs[iBatches[i]*vocabSize : (iBatches[i]+1)*vocabSize])
 		if err != nil {
-			s.hardErrCh <- fmt.Errorf("failed to sample token: %w", err)
-			return
+			panic("failed to sample token")
 		}
 
 		nextBatchTokens[i].Token = token
@@ -747,8 +749,7 @@ func (s *Server) computeBatch(activeBatch batchState) {
 
 		piece, err := s.model.(model.TextProcessor).Decode([]int32{token})
 		if err != nil {
-			s.hardErrCh <- fmt.Errorf("failed to decode token: %w", err)
-			return
+			panic("failed to decode token")
 		}
 
 		seq.pendingResponses = append(seq.pendingResponses, piece)
@@ -793,6 +794,13 @@ func (s *Server) computeBatch(activeBatch batchState) {
 			s.removeSequence(i, llm.DoneReasonConnectionClosed)
 		}
 	}
+
+	samplingDuration := time.Since(t)
+	for i, seq := range s.seqs {
+		if seq != nil && nextBatchTokens[i] != nil {
+			s.seqs[i].samplingDuration += samplingDuration
+		}
+	}
 }
 
 func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
@@ -912,9 +920,9 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 					Done:               true,
 					DoneReason:         seq.doneReason,
 					PromptEvalCount:    seq.numPromptInputs,
-					PromptEvalDuration: seq.startGenerationTime.Sub(seq.startProcessingTime),
+					PromptEvalDuration: seq.processingDuration,
 					EvalCount:          seq.numPredicted,
-					EvalDuration:       time.Since(seq.startGenerationTime),
+					EvalDuration:       seq.lastUpdatedAt.Sub(seq.startedAt) - seq.samplingDuration,
 				}); err != nil {
 					http.Error(w, fmt.Sprintf("failed to encode final response: %v", err), http.StatusInternalServerError)
 				}
@@ -1329,7 +1337,6 @@ func Execute(args []string) error {
 	server := &Server{
 		modelPath: *mpath,
 		status:    llm.ServerStatusLaunched,
-		hardErrCh: make(chan error, 1),
 	}
 
 	server.cond = sync.NewCond(&server.mu)

server/routes.go

@@ -332,14 +332,16 @@ func (s *Server) GenerateHandler(c *gin.Context) {
 	}
 
 	modelCaps := m.Capabilities()
-	if req.Think != nil {
+	if slices.Contains(modelCaps, model.CapabilityThinking) {
 		caps = append(caps, model.CapabilityThinking)
-	} else {
-		// add thinking if the model supports it
-		if slices.Contains(modelCaps, model.CapabilityThinking) {
-			caps = append(caps, model.CapabilityThinking)
+		if req.Think == nil {
 			req.Think = &api.ThinkValue{Value: true}
 		}
+	} else {
+		if req.Think != nil && req.Think.Bool() {
+			c.JSON(http.StatusBadRequest, gin.H{"error": fmt.Sprintf("%q does not support thinking", req.Model)})
+			return
+		}
 	}
 
 	r, m, opts, err := s.scheduleRunner(c.Request.Context(), name.String(), caps, req.Options, req.KeepAlive)
@@ -401,12 +403,11 @@ func (s *Server) GenerateHandler(c *gin.Context) {
 				msgs = append(msgs, m.Messages...)
 			}
 
+			userMsg := api.Message{Role: "user", Content: req.Prompt}
 			for _, i := range images {
-				imgPrompt := ""
-				msgs = append(msgs, api.Message{Role: "user", Content: fmt.Sprintf("[img-%d]"+imgPrompt, i.ID)})
+				userMsg.Images = append(userMsg.Images, i.Data)
 			}
-
-			values.Messages = append(msgs, api.Message{Role: "user", Content: req.Prompt})
+			values.Messages = append(msgs, userMsg)
 		}
 
 		values.Think = req.Think != nil && req.Think.Bool()
@@ -427,12 +428,31 @@ func (s *Server) GenerateHandler(c *gin.Context) {
 			b.WriteString(s)
 		}
 
-		if err := tmpl.Execute(&b, values); err != nil {
-			c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
-			return
-		}
+		// check that we're in the `api/chat`-like flow, and if so, generate the
+		// prompt the same way
+		// TEMP(drifkin): we should really just detect the chat-like flow and call
+		// the real chat handler, but doing this as a stopgap to get renderer
+		// support for generate
+		if values.Messages != nil && values.Suffix == "" && req.Template == "" {
+			prompt, images, err = chatPrompt(c.Request.Context(), m, r.Tokenize, opts, values.Messages, []api.Tool{}, req.Think, req.Truncate == nil || *req.Truncate)
+			if err != nil {
+				c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
+				return
+			}
+			// TEMP(drifkin): req.Context will be removed very soon, but we're temporarily supporting it in this flow here
+			if req.Context != nil {
+				b.WriteString(prompt)
+				prompt = b.String()
+			}
+		} else {
+			// legacy flow
+			if err := tmpl.Execute(&b, values); err != nil {
+				c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
+				return
+			}
 
-		prompt = b.String()
+			prompt = b.String()
+		}
 	}
 
 	// If debug mode is enabled, return the rendered template instead of calling the model
@@ -535,7 +555,12 @@ func (s *Server) GenerateHandler(c *gin.Context) {
 
 			ch <- res
 		}); err != nil {
-			ch <- err
+			var serr api.StatusError
+			if errors.As(err, &serr) {
+				ch <- gin.H{"error": serr.ErrorMessage, "status": serr.StatusCode}
+			} else {
+				ch <- gin.H{"error": err.Error()}
+			}
 		}
 	}()
 
@@ -549,20 +574,18 @@ func (s *Server) GenerateHandler(c *gin.Context) {
 				sbThinking.WriteString(t.Thinking)
 				sbContent.WriteString(t.Response)
 				r = t
-			case api.StatusError:
-				c.JSON(t.StatusCode, gin.H{"error": t.ErrorMessage})
-				return
-			case error:
-				c.JSON(http.StatusInternalServerError, gin.H{"error": t.Error()})
-				return
-			// TODO (jmorganca): remove use of gin.H here and instead expect
-			// api.StatusError to be send in the channel
 			case gin.H:
-				if msg, ok := t["error"].(string); ok {
-					c.JSON(http.StatusInternalServerError, gin.H{"error": msg})
-					return
+				msg, ok := t["error"].(string)
+				if !ok {
+					msg = "unexpected error format in response"
 				}
-				c.JSON(http.StatusInternalServerError, gin.H{"error": "unexpected response"})
+
+				status, ok := t["status"].(int)
+				if !ok {
+					status = http.StatusInternalServerError
+				}
+
+				c.JSON(status, gin.H{"error": msg})
 				return
 			default:
 				c.JSON(http.StatusInternalServerError, gin.H{"error": "unexpected response"})
@@ -1627,16 +1650,28 @@ func streamResponse(c *gin.Context, ch chan any) {
 			return false
 		}
 
-		if statusError, ok := val.(api.StatusError); ok {
-			c.Header("Content-Type", "application/json")
-			c.AbortWithStatusJSON(statusError.StatusCode, gin.H{"error": statusError.ErrorMessage})
-			return false
-		}
+		// errors are provided as a gin.H with an "error" field and
+		// an optional "status" field.  For errors that are streamed
+		// before any content, we need to set the status code and
+		// content type for the error.
+		if h, ok := val.(gin.H); ok {
+			if e, ok := h["error"].(string); ok {
+				status, ok := h["status"].(int)
+				if !ok {
+					status = http.StatusInternalServerError
+				}
 
-		if err, ok := val.(error); ok {
-			c.Header("Content-Type", "application/json")
-			c.AbortWithStatusJSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
-			return false
+				if !c.Writer.Written() {
+					c.Header("Content-Type", "application/json")
+					c.JSON(status, gin.H{"error": e})
+				} else {
+					if err := json.NewEncoder(c.Writer).Encode(gin.H{"error": e}); err != nil {
+						slog.Error("streamResponse failed to encode json error", "error", err)
+					}
+				}
+
+				return false
+			}
 		}
 
 		bts, err := json.Marshal(val)
@@ -1898,14 +1933,16 @@ func (s *Server) ChatHandler(c *gin.Context) {
 	}
 
 	modelCaps := m.Capabilities()
-	if req.Think != nil {
+	if slices.Contains(modelCaps, model.CapabilityThinking) {
 		caps = append(caps, model.CapabilityThinking)
-	} else {
-		// add thinking if the model supports it
-		if slices.Contains(modelCaps, model.CapabilityThinking) {
-			caps = append(caps, model.CapabilityThinking)
+		if req.Think == nil {
 			req.Think = &api.ThinkValue{Value: true}
 		}
+	} else {
+		if req.Think != nil && req.Think.Bool() {
+			c.JSON(http.StatusBadRequest, gin.H{"error": fmt.Sprintf("%q does not support thinking", req.Model)})
+			return
+		}
 	}
 
 	r, m, opts, err := s.scheduleRunner(c.Request.Context(), name.String(), caps, req.Options, req.KeepAlive)
@@ -2001,90 +2038,174 @@ func (s *Server) ChatHandler(c *gin.Context) {
 		toolParser = tools.NewParser(m.Template.Template, req.Tools)
 	}
 
+	type structuredOutputsState int
+	const (
+		structuredOutputsState_None structuredOutputsState = iota
+		structuredOutputsState_ReadyToApply
+		structuredOutputsState_Applying
+	)
+
 	ch := make(chan any)
 	go func() {
 		defer close(ch)
 
-		if err := r.Completion(c.Request.Context(), llm.CompletionRequest{
-			Prompt:   prompt,
-			Images:   images,
-			Format:   req.Format,
-			Options:  opts,
-			Shift:    req.Shift == nil || *req.Shift,
-			Truncate: truncate,
-		}, func(r llm.CompletionResponse) {
-			res := api.ChatResponse{
-				Model:     req.Model,
-				CreatedAt: time.Now().UTC(),
-				Message:   api.Message{Role: "assistant", Content: r.Content},
-				Done:      r.Done,
-				Metrics: api.Metrics{
-					PromptEvalCount:    r.PromptEvalCount,
-					PromptEvalDuration: r.PromptEvalDuration,
-					EvalCount:          r.EvalCount,
-					EvalDuration:       r.EvalDuration,
-				},
-			}
-			if r.Done {
-				res.DoneReason = r.DoneReason.String()
-				res.TotalDuration = time.Since(checkpointStart)
-				res.LoadDuration = checkpointLoaded.Sub(checkpointStart)
+		structuredOutputsState := structuredOutputsState_None
+
+		for {
+			var tb strings.Builder
+
+			currentFormat := req.Format
+			// structured outputs via double request is enabled when:
+			// 1. the model supports the thinking capability and
+			// 2. it uses a built-in parser or our generic thinking parser
+
+			// Note that the current approach does not work for (potential future)
+			// non-thinking models that emit anything before actual content. This
+			// current approach uses the transition from parsed thinking content to
+			// parsed non-thinking content as the signal to turn constraining on
+
+			if req.Format != nil && structuredOutputsState == structuredOutputsState_None && ((builtinParser != nil || thinkingState != nil) && slices.Contains(m.Capabilities(), model.CapabilityThinking)) {
+				currentFormat = nil
 			}
 
-			if builtinParser != nil {
-				slog.Log(context.TODO(), logutil.LevelTrace, "builtin parser input", "parser", m.Config.Parser, "content", r.Content)
-
-				content, thinking, toolCalls, err := builtinParser.Add(r.Content, r.Done)
-				if err != nil {
-					ch <- gin.H{"error": err.Error()}
-					return
+			// sets up new context given parent context per request
+			ctx, cancel := context.WithCancel(c.Request.Context())
+			err := r.Completion(ctx, llm.CompletionRequest{
+				Prompt:   prompt,
+				Images:   images,
+				Format:   currentFormat,
+				Options:  opts,
+				Shift:    req.Shift == nil || *req.Shift,
+				Truncate: truncate,
+			}, func(r llm.CompletionResponse) {
+				res := api.ChatResponse{
+					Model:     req.Model,
+					CreatedAt: time.Now().UTC(),
+					Message:   api.Message{Role: "assistant", Content: r.Content},
+					Done:      r.Done,
+					Metrics: api.Metrics{
+						PromptEvalCount:    r.PromptEvalCount,
+						PromptEvalDuration: r.PromptEvalDuration,
+						EvalCount:          r.EvalCount,
+						EvalDuration:       r.EvalDuration,
+					},
+				}
+				if r.Done {
+					res.DoneReason = r.DoneReason.String()
+					res.TotalDuration = time.Since(checkpointStart)
+					res.LoadDuration = checkpointLoaded.Sub(checkpointStart)
 				}
 
-				res.Message.Content = content
-				res.Message.Thinking = thinking
-				res.Message.ToolCalls = toolCalls
+				if builtinParser != nil {
+					slog.Log(context.TODO(), logutil.LevelTrace, "builtin parser input", "parser", m.Config.Parser, "content", r.Content)
 
-				if res.Message.Content != "" || res.Message.Thinking != "" || len(res.Message.ToolCalls) > 0 || r.Done {
-					slog.Log(context.TODO(), logutil.LevelTrace, "builtin parser output", "parser", m.Config.Parser, "content", content, "thinking", thinking, "toolCalls", toolCalls, "done", r.Done)
-					ch <- res
-				} else {
-					slog.Log(context.TODO(), logutil.LevelTrace, "builtin parser empty output", "parser", m.Config.Parser)
-				}
+					content, thinking, toolCalls, err := builtinParser.Add(r.Content, r.Done)
+					if err != nil {
+						ch <- gin.H{"error": err.Error()}
+						return
+					}
 
-				return
-			}
-
-			if thinkingState != nil {
-				thinkingContent, remainingContent := thinkingState.AddContent(res.Message.Content)
-				if thinkingContent == "" && remainingContent == "" && !r.Done {
-					// need to accumulate more to decide what to send
-					return
-				}
-				res.Message.Content = remainingContent
-				res.Message.Thinking = thinkingContent
-			}
-
-			if len(req.Tools) > 0 {
-				toolCalls, content := toolParser.Add(res.Message.Content)
-				if len(content) > 0 {
 					res.Message.Content = content
-				} else if len(toolCalls) > 0 {
+					res.Message.Thinking = thinking
 					res.Message.ToolCalls = toolCalls
-					res.Message.Content = ""
-				} else if res.Message.Thinking != "" {
-					// don't return
-				} else {
-					if r.Done {
-						res.Message.Content = toolParser.Content()
+
+					tb.WriteString(thinking)
+					// we are now receiving content from the model - we should start applying structured outputs
+					if structuredOutputsState == structuredOutputsState_None && req.Format != nil && tb.String() != "" && res.Message.Content != "" {
+						structuredOutputsState = structuredOutputsState_ReadyToApply
+						cancel()
+						return
+					}
+
+					if res.Message.Content != "" || res.Message.Thinking != "" || len(res.Message.ToolCalls) > 0 || r.Done {
+						slog.Log(context.TODO(), logutil.LevelTrace, "builtin parser output", "parser", m.Config.Parser, "content", content, "thinking", thinking, "toolCalls", toolCalls, "done", r.Done)
 						ch <- res
+					} else {
+						slog.Log(context.TODO(), logutil.LevelTrace, "builtin parser empty output", "parser", m.Config.Parser)
+					}
+					return
+				}
+
+				if thinkingState != nil {
+					thinkingContent, remainingContent := thinkingState.AddContent(res.Message.Content)
+					if thinkingContent == "" && remainingContent == "" && !r.Done {
+						// need to accumulate more to decide what to send
+						return
+					}
+					res.Message.Thinking = thinkingContent
+					tb.WriteString(thinkingContent)
+					// emit the collected thinking text before restarting with structured outputs and clear unstructured content
+					// to avoid leaking mixed tokens like "</think>Hello"
+					if structuredOutputsState == structuredOutputsState_None && req.Format != nil && tb.String() != "" && remainingContent != "" {
+						structuredOutputsState = structuredOutputsState_ReadyToApply
+						res.Message.Content = ""
+						ch <- res
+						cancel()
+						return
+					}
+					res.Message.Content = remainingContent
+				}
+
+				if len(req.Tools) > 0 {
+					toolCalls, content := toolParser.Add(res.Message.Content)
+					if len(content) > 0 {
+						res.Message.Content = content
+					} else if len(toolCalls) > 0 {
+						res.Message.ToolCalls = toolCalls
+						res.Message.Content = ""
+					} else if res.Message.Thinking != "" {
+						// don't return
+					} else {
+						if r.Done {
+							res.Message.Content = toolParser.Content()
+							ch <- res
+						}
+						return
+					}
+				}
+
+				ch <- res
+			})
+			if err != nil {
+				if structuredOutputsState == structuredOutputsState_ReadyToApply && strings.Contains(err.Error(), "context canceled") && c.Request.Context().Err() == nil {
+					// only ignores error if it's a context cancellation due to setting structured outputs
+				} else {
+					var serr api.StatusError
+					if errors.As(err, &serr) {
+						ch <- gin.H{"error": serr.ErrorMessage, "status": serr.StatusCode}
+					} else {
+						ch <- gin.H{"error": err.Error()}
 					}
 					return
 				}
 			}
 
-			ch <- res
-		}); err != nil {
-			ch <- err
+			// ignored structured outputs cancellation falls through to here, start a new request with the structured outputs and updated prompt. use the
+			if structuredOutputsState == structuredOutputsState_ReadyToApply {
+				structuredOutputsState = structuredOutputsState_Applying
+				msg := api.Message{
+					Role:     "assistant",
+					Thinking: tb.String(),
+				}
+
+				msgs = append(msgs, msg)
+				prompt, _, err = chatPrompt(c.Request.Context(), m, r.Tokenize, opts, msgs, processedTools, req.Think, truncate)
+				if err != nil {
+					slog.Error("chat prompt error applying structured outputs", "error", err)
+					ch <- gin.H{"error": err.Error()}
+					return
+				}
+				// force constraining by terminating thinking header, the parser is already at this state
+				// when the last message is thinking, the rendered for gpt-oss cannot disambiguate between having the
+				// model continue thinking or ending thinking and outputting the final message.
+				// TODO(parthsareen): consider adding prefill disambiguation logic to the renderer for structured outputs.
+				if shouldUseHarmony(m) || (builtinParser != nil && m.Config.Parser == "harmony") {
+					prompt += "<|end|><|start|>assistant<|channel|>final<|message|>"
+				}
+				continue
+			}
+
+			break
 		}
 	}()
 
@@ -2102,20 +2223,18 @@ func (s *Server) ChatHandler(c *gin.Context) {
 				if len(req.Tools) > 0 {
 					toolCalls = append(toolCalls, t.Message.ToolCalls...)
 				}
-			case api.StatusError:
-				c.JSON(t.StatusCode, gin.H{"error": t.ErrorMessage})
-				return
-			case error:
-				c.JSON(http.StatusInternalServerError, gin.H{"error": t.Error()})
-				return
-			// TODO (jmorganca): remove use of gin.H here and instead expect
-			// api.StatusError to be send in the channel
 			case gin.H:
-				if msg, ok := t["error"].(string); ok {
-					c.JSON(http.StatusInternalServerError, gin.H{"error": msg})
-					return
+				msg, ok := t["error"].(string)
+				if !ok {
+					msg = "unexpected error format in response"
 				}
-				c.JSON(http.StatusInternalServerError, gin.H{"error": "unexpected response"})
+
+				status, ok := t["status"].(int)
+				if !ok {
+					status = http.StatusInternalServerError
+				}
+
+				c.JSON(status, gin.H{"error": msg})
 				return
 			default:
 				c.JSON(http.StatusInternalServerError, gin.H{"error": "unexpected response"})

server/routes_debug_test.go

@@ -146,7 +146,7 @@ func TestGenerateDebugRenderOnly(t *testing.T) {
 				DebugRenderOnly: true,
 			},
 			expectDebug:     true,
-			expectTemplate:  "[img-0]\n\nDescribe this image",
+			expectTemplate:  "[img-0]Describe this image",
 			expectNumImages: 1,
 		},
 		{

server/routes_generate_renderer_test.go

@@ -0,0 +1,313 @@
+package server
+
+import (
+	"bytes"
+	"encoding/json"
+	"net/http"
+	"strings"
+	"testing"
+	"time"
+
+	"github.com/gin-gonic/gin"
+	"github.com/google/go-cmp/cmp"
+
+	"github.com/ollama/ollama/api"
+	"github.com/ollama/ollama/discover"
+	"github.com/ollama/ollama/fs/ggml"
+	"github.com/ollama/ollama/llm"
+)
+
+// TestGenerateWithBuiltinRenderer tests that api/generate uses built-in renderers
+// when in chat-like flow (messages present, no suffix, no template)
+func TestGenerateWithBuiltinRenderer(t *testing.T) {
+	gin.SetMode(gin.TestMode)
+
+	mock := mockRunner{
+		CompletionResponse: llm.CompletionResponse{
+			Done:               true,
+			DoneReason:         llm.DoneReasonStop,
+			PromptEvalCount:    1,
+			PromptEvalDuration: 1,
+			EvalCount:          1,
+			EvalDuration:       1,
+		},
+	}
+
+	s := Server{
+		sched: &Scheduler{
+			pendingReqCh:  make(chan *LlmRequest, 1),
+			finishedReqCh: make(chan *LlmRequest, 1),
+			expiredCh:     make(chan *runnerRef, 1),
+			unloadedCh:    make(chan any, 1),
+			loaded:        make(map[string]*runnerRef),
+			newServerFn:   newMockServer(&mock),
+			getGpuFn:      getGpuFn,
+			getCpuFn:      getCpuFn,
+			reschedDelay:  250 * time.Millisecond,
+			loadFn: func(req *LlmRequest, _ *ggml.GGML, _ discover.GpuInfoList, _ bool) bool {
+				time.Sleep(time.Millisecond)
+				req.successCh <- &runnerRef{
+					llama: &mock,
+				}
+				return false
+			},
+		},
+	}
+
+	go s.sched.Run(t.Context())
+
+	// Create a model with a built-in renderer (qwen3-coder)
+	_, digest := createBinFile(t, ggml.KV{
+		"general.architecture":          "qwen3",
+		"qwen3.block_count":             uint32(1),
+		"qwen3.context_length":          uint32(8192),
+		"qwen3.embedding_length":        uint32(4096),
+		"qwen3.attention.head_count":    uint32(32),
+		"qwen3.attention.head_count_kv": uint32(8),
+		"tokenizer.ggml.tokens":         []string{""},
+		"tokenizer.ggml.scores":         []float32{0},
+		"tokenizer.ggml.token_type":     []int32{0},
+	}, []*ggml.Tensor{
+		{Name: "token_embd.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+		{Name: "blk.0.attn_norm.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+		{Name: "blk.0.ffn_down.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+		{Name: "blk.0.ffn_gate.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+		{Name: "blk.0.ffn_up.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+		{Name: "blk.0.ffn_norm.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+		{Name: "blk.0.attn_k.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+		{Name: "blk.0.attn_output.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+		{Name: "blk.0.attn_q.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+		{Name: "blk.0.attn_v.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+		{Name: "output.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+	})
+
+	// Create a model with the qwen3-coder renderer
+	w := createRequest(t, s.CreateHandler, api.CreateRequest{
+		Model:    "test-renderer",
+		Files:    map[string]string{"file.gguf": digest},
+		Renderer: "qwen3-coder",
+		Stream:   &stream,
+	})
+
+	if w.Code != http.StatusOK {
+		t.Fatalf("expected status 200, got %d", w.Code)
+	}
+
+	mock.CompletionResponse.Content = "Hi!"
+
+	t.Run("chat-like flow uses renderer", func(t *testing.T) {
+		// Test that when using messages (chat-like flow), the built-in renderer is used
+		w := createRequest(t, s.GenerateHandler, api.GenerateRequest{
+			Model:  "test-renderer",
+			Prompt: "Write a hello world function",
+			Stream: &stream,
+		})
+
+		if w.Code != http.StatusOK {
+			t.Errorf("expected status 200, got %d", w.Code)
+		}
+
+		// The qwen3-coder renderer produces output with <|im_start|> and <|im_end|> tags
+		// When messages are built internally from prompt, it should use the renderer
+		if !strings.Contains(mock.CompletionRequest.Prompt, "<|im_start|>") {
+			t.Errorf("expected prompt to contain <|im_start|> from qwen3-coder renderer, got: %s", mock.CompletionRequest.Prompt)
+		}
+
+		if !strings.Contains(mock.CompletionRequest.Prompt, "<|im_end|>") {
+			t.Errorf("expected prompt to contain <|im_end|> from qwen3-coder renderer, got: %s", mock.CompletionRequest.Prompt)
+		}
+	})
+
+	t.Run("chat-like flow with system message uses renderer", func(t *testing.T) {
+		// Test that system messages work with the renderer
+		w := createRequest(t, s.GenerateHandler, api.GenerateRequest{
+			Model:  "test-renderer",
+			Prompt: "Write a hello world function",
+			System: "You are a helpful coding assistant.",
+			Stream: &stream,
+		})
+
+		if w.Code != http.StatusOK {
+			t.Errorf("expected status 200, got %d", w.Code)
+		}
+
+		// Should contain the system message and use renderer format
+		if !strings.Contains(mock.CompletionRequest.Prompt, "<|im_start|>system") {
+			t.Errorf("expected prompt to contain system message with renderer format, got: %s", mock.CompletionRequest.Prompt)
+		}
+
+		if !strings.Contains(mock.CompletionRequest.Prompt, "You are a helpful coding assistant.") {
+			t.Errorf("expected prompt to contain system message content, got: %s", mock.CompletionRequest.Prompt)
+		}
+	})
+
+	t.Run("custom template bypasses renderer", func(t *testing.T) {
+		// Test that providing a custom template uses the legacy flow
+		w := createRequest(t, s.GenerateHandler, api.GenerateRequest{
+			Model:    "test-renderer",
+			Prompt:   "Write a hello world function",
+			Template: "{{ .Prompt }}",
+			Stream:   &stream,
+		})
+
+		if w.Code != http.StatusOK {
+			t.Errorf("expected status 200, got %d", w.Code)
+		}
+
+		// Should NOT use the renderer format when custom template is provided
+		if strings.Contains(mock.CompletionRequest.Prompt, "<|im_start|>") {
+			t.Errorf("expected prompt to NOT use renderer when custom template provided, got: %s", mock.CompletionRequest.Prompt)
+		}
+
+		// Should just be the raw prompt from the template
+		if diff := cmp.Diff(mock.CompletionRequest.Prompt, "Write a hello world function"); diff != "" {
+			t.Errorf("mismatch (-got +want):\n%s", diff)
+		}
+	})
+
+	// Create a model with suffix support for the next test
+	w = createRequest(t, s.CreateHandler, api.CreateRequest{
+		Model: "test-suffix-renderer",
+		From:  "test-renderer",
+		Template: `{{- if .Suffix }}<PRE> {{ .Prompt }} <SUF>{{ .Suffix }} <MID>
+{{- else }}{{ .Prompt }}
+{{- end }}`,
+	})
+
+	if w.Code != http.StatusOK {
+		t.Fatalf("expected status 200, got %d", w.Code)
+	}
+
+	t.Run("suffix bypasses renderer", func(t *testing.T) {
+		// Test that providing a suffix uses the legacy flow
+		w := createRequest(t, s.GenerateHandler, api.GenerateRequest{
+			Model:  "test-suffix-renderer",
+			Prompt: "def add(",
+			Suffix: "    return c",
+		})
+
+		if w.Code != http.StatusOK {
+			t.Errorf("expected status 200, got %d", w.Code)
+		}
+
+		// Should NOT use the renderer format when suffix is provided
+		if strings.Contains(mock.CompletionRequest.Prompt, "<|im_start|>") {
+			t.Errorf("expected prompt to NOT use renderer when suffix provided, got: %s", mock.CompletionRequest.Prompt)
+		}
+
+		// Should use the suffix template format
+		if diff := cmp.Diff(mock.CompletionRequest.Prompt, "<PRE> def add( <SUF>    return c <MID>"); diff != "" {
+			t.Errorf("mismatch (-got +want):\n%s", diff)
+		}
+	})
+}
+
+// TestGenerateWithDebugRenderOnly tests that debug_render_only works with built-in renderers
+func TestGenerateWithDebugRenderOnly(t *testing.T) {
+	gin.SetMode(gin.TestMode)
+
+	mock := mockRunner{
+		CompletionResponse: llm.CompletionResponse{
+			Done:               true,
+			DoneReason:         llm.DoneReasonStop,
+			PromptEvalCount:    1,
+			PromptEvalDuration: 1,
+			EvalCount:          1,
+			EvalDuration:       1,
+		},
+	}
+
+	s := Server{
+		sched: &Scheduler{
+			pendingReqCh:  make(chan *LlmRequest, 1),
+			finishedReqCh: make(chan *LlmRequest, 1),
+			expiredCh:     make(chan *runnerRef, 1),
+			unloadedCh:    make(chan any, 1),
+			loaded:        make(map[string]*runnerRef),
+			newServerFn:   newMockServer(&mock),
+			getGpuFn:      getGpuFn,
+			getCpuFn:      getCpuFn,
+			reschedDelay:  250 * time.Millisecond,
+			loadFn: func(req *LlmRequest, _ *ggml.GGML, _ discover.GpuInfoList, _ bool) bool {
+				time.Sleep(time.Millisecond)
+				req.successCh <- &runnerRef{
+					llama: &mock,
+				}
+				return false
+			},
+		},
+	}
+
+	go s.sched.Run(t.Context())
+
+	// Create a model with a built-in renderer
+	_, digest := createBinFile(t, ggml.KV{
+		"general.architecture":          "qwen3",
+		"qwen3.block_count":             uint32(1),
+		"qwen3.context_length":          uint32(8192),
+		"qwen3.embedding_length":        uint32(4096),
+		"qwen3.attention.head_count":    uint32(32),
+		"qwen3.attention.head_count_kv": uint32(8),
+		"tokenizer.ggml.tokens":         []string{""},
+		"tokenizer.ggml.scores":         []float32{0},
+		"tokenizer.ggml.token_type":     []int32{0},
+	}, []*ggml.Tensor{
+		{Name: "token_embd.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+		{Name: "blk.0.attn_norm.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+		{Name: "blk.0.ffn_down.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+		{Name: "blk.0.ffn_gate.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+		{Name: "blk.0.ffn_up.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+		{Name: "blk.0.ffn_norm.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+		{Name: "blk.0.attn_k.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+		{Name: "blk.0.attn_output.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+		{Name: "blk.0.attn_q.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+		{Name: "blk.0.attn_v.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+		{Name: "output.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+	})
+
+	w := createRequest(t, s.CreateHandler, api.CreateRequest{
+		Model:    "test-debug-renderer",
+		Files:    map[string]string{"file.gguf": digest},
+		Renderer: "qwen3-coder",
+		Stream:   &stream,
+	})
+
+	if w.Code != http.StatusOK {
+		t.Fatalf("expected status 200, got %d", w.Code)
+	}
+
+	t.Run("debug_render_only with renderer", func(t *testing.T) {
+		w := createRequest(t, s.GenerateHandler, api.GenerateRequest{
+			Model:           "test-debug-renderer",
+			Prompt:          "Write a hello world function",
+			System:          "You are a coding assistant",
+			DebugRenderOnly: true,
+		})
+
+		if w.Code != http.StatusOK {
+			t.Errorf("expected status 200, got %d", w.Code)
+		}
+
+		var resp api.GenerateResponse
+		if err := json.NewDecoder(w.Body).Decode(&resp); err != nil {
+			t.Fatal(err)
+		}
+
+		if resp.DebugInfo == nil {
+			t.Fatalf("expected debug info, got nil")
+		}
+
+		// Verify that the rendered template uses the built-in renderer
+		if !strings.Contains(resp.DebugInfo.RenderedTemplate, "<|im_start|>") {
+			t.Errorf("expected rendered template to use qwen3-coder renderer format, got: %s", resp.DebugInfo.RenderedTemplate)
+		}
+
+		if !strings.Contains(resp.DebugInfo.RenderedTemplate, "You are a coding assistant") {
+			t.Errorf("expected rendered template to contain system message, got: %s", resp.DebugInfo.RenderedTemplate)
+		}
+
+		if !strings.Contains(resp.DebugInfo.RenderedTemplate, "Write a hello world function") {
+			t.Errorf("expected rendered template to contain prompt, got: %s", resp.DebugInfo.RenderedTemplate)
+		}
+	})
+}

server/routes_generate_test.go

@@ -158,11 +158,26 @@ func TestGenerateChat(t *testing.T) {
 			t.Errorf("expected status 400, got %d", w.Code)
 		}
 
-		if diff := cmp.Diff(w.Body.String(), `{"error":"registry.ollama.ai/library/test:latest does not support thinking"}`); diff != "" {
+		if diff := cmp.Diff(w.Body.String(), `{"error":"\"test\" does not support thinking"}`); diff != "" {
 			t.Errorf("mismatch (-got +want):\n%s", diff)
 		}
 	})
 
+	t.Run("model can't think but think set false", func(t *testing.T) {
+		think := false
+		w := createRequest(t, s.ChatHandler, api.ChatRequest{
+			Model: "test",
+			Messages: []api.Message{
+				{Role: "user", Content: "Hello!"},
+			},
+			Think: &api.ThinkValue{Value: think},
+		})
+
+		if w.Code != http.StatusOK {
+			t.Errorf("expected status 200, got %d", w.Code)
+		}
+	})
+
 	t.Run("missing model", func(t *testing.T) {
 		w := createRequest(t, s.ChatHandler, api.ChatRequest{})
 		if w.Code != http.StatusBadRequest {
@@ -1292,4 +1307,238 @@ func TestChatWithPromptEndingInThinkTag(t *testing.T) {
 			t.Errorf("expected content %q, got %q", "Based on my analysis, the solution is straightforward.", got)
 		}
 	})
+
+	t.Run("structured outputs restart non-stream", func(t *testing.T) {
+		var (
+			requestsMu sync.Mutex
+			requests   []llm.CompletionRequest
+			wg         sync.WaitGroup
+		)
+
+		wg.Add(2)
+
+		format := json.RawMessage(`{"type":"object","properties":{"answer":{"type":"string"}}}`)
+
+		mock.CompletionFn = func(ctx context.Context, r llm.CompletionRequest, fn func(r llm.CompletionResponse)) error {
+			defer wg.Done()
+
+			requestsMu.Lock()
+			requests = append(requests, r)
+			callNum := len(requests)
+			requestsMu.Unlock()
+
+			switch callNum {
+			case 1:
+				fn(llm.CompletionResponse{
+					Content:            " I am thinking through this problem. </think> {\"answer\":\"42\"}",
+					Done:               false,
+					PromptEvalCount:    1,
+					PromptEvalDuration: 1,
+				})
+
+				select {
+				case <-ctx.Done():
+					return ctx.Err()
+				case <-time.After(time.Second):
+					t.Fatalf("timeout waiting for structured outputs cancellation")
+					return nil
+				}
+			case 2:
+				fn(llm.CompletionResponse{
+					Content:            `{"answer":"42"}`,
+					Done:               true,
+					DoneReason:         llm.DoneReasonStop,
+					PromptEvalCount:    1,
+					PromptEvalDuration: 1,
+					EvalCount:          1,
+					EvalDuration:       1,
+				})
+				return nil
+			default:
+				t.Fatalf("unexpected number of completion calls: %d", callNum)
+				return nil
+			}
+		}
+
+		think := true
+		streamRequest := false
+		w := createRequest(t, s.ChatHandler, api.ChatRequest{
+			Model:    "test-thinking",
+			Messages: []api.Message{{Role: "user", Content: "Please respond in JSON."}},
+			Think:    &api.ThinkValue{Value: think},
+			Stream:   &streamRequest,
+			Format:   format,
+		})
+
+		wg.Wait()
+		mock.CompletionFn = nil
+
+		if w.Code != http.StatusOK {
+			t.Fatalf("expected status 200, got %d", w.Code)
+		}
+
+		if len(requests) != 2 {
+			t.Fatalf("expected two completion calls, got %d", len(requests))
+		}
+
+		if requests[0].Format != nil {
+			t.Errorf("expected first completion format to be nil, got %q", requests[0].Format)
+		}
+
+		if !bytes.Equal([]byte(format), []byte(requests[1].Format)) {
+			t.Errorf("expected second completion format to match original format")
+		}
+
+		var resp api.ChatResponse
+		if err := json.NewDecoder(w.Body).Decode(&resp); err != nil {
+			t.Fatal(err)
+		}
+
+		if resp.Message.Thinking != "I am thinking through this problem. " {
+			t.Errorf("expected thinking %q, got %q", "I am thinking through this problem. ", resp.Message.Thinking)
+		}
+
+		if resp.Message.Content != `{"answer":"42"}` {
+			t.Errorf("expected content %q, got %q", `{"answer":"42"}`, resp.Message.Content)
+		}
+
+		if !resp.Done {
+			t.Errorf("expected response to be done")
+		}
+
+		if resp.DoneReason != "stop" {
+			t.Errorf("expected done reason stop, got %s", resp.DoneReason)
+		}
+	})
+
+	t.Run("structured outputs restart streaming", func(t *testing.T) {
+		var (
+			requestsMu sync.Mutex
+			requests   []llm.CompletionRequest
+			wg         sync.WaitGroup
+		)
+
+		wg.Add(2)
+
+		format := json.RawMessage(`{"type":"object","properties":{"answer":{"type":"string"}}}`)
+
+		mock.CompletionFn = func(ctx context.Context, r llm.CompletionRequest, fn func(r llm.CompletionResponse)) error {
+			defer wg.Done()
+
+			requestsMu.Lock()
+			requests = append(requests, r)
+			callNum := len(requests)
+			requestsMu.Unlock()
+
+			switch callNum {
+			case 1:
+				fn(llm.CompletionResponse{
+					Content:            " I am thinking through this problem. </think> {\"answer\":\"42\"}",
+					Done:               false,
+					PromptEvalCount:    1,
+					PromptEvalDuration: 1,
+				})
+
+				select {
+				case <-ctx.Done():
+					return ctx.Err()
+				case <-time.After(time.Second):
+					t.Fatalf("timeout waiting for structured outputs cancellation")
+					return nil
+				}
+			case 2:
+				fn(llm.CompletionResponse{
+					Content:            `{"answer":"42"}`,
+					Done:               true,
+					DoneReason:         llm.DoneReasonStop,
+					PromptEvalCount:    1,
+					PromptEvalDuration: 1,
+					EvalCount:          1,
+					EvalDuration:       1,
+				})
+				return nil
+			default:
+				t.Fatalf("unexpected number of completion calls: %d", callNum)
+				return nil
+			}
+		}
+
+		think := true
+		streamRequest := true
+		w := createRequest(t, s.ChatHandler, api.ChatRequest{
+			Model:    "test-thinking",
+			Messages: []api.Message{{Role: "user", Content: "Please respond in JSON."}},
+			Think:    &api.ThinkValue{Value: think},
+			Stream:   &streamRequest,
+			Format:   format,
+		})
+
+		wg.Wait()
+		mock.CompletionFn = nil
+
+		if w.Code != http.StatusOK {
+			t.Fatalf("expected status 200, got %d", w.Code)
+		}
+
+		if len(requests) != 2 {
+			t.Fatalf("expected two completion calls, got %d", len(requests))
+		}
+
+		if requests[0].Format != nil {
+			t.Errorf("expected first completion format to be nil, got %q", requests[0].Format)
+		}
+
+		if !bytes.Equal([]byte(format), []byte(requests[1].Format)) {
+			t.Errorf("expected second completion format to match original format")
+		}
+
+		decoder := json.NewDecoder(w.Body)
+		var events []api.ChatResponse
+		for {
+			var event api.ChatResponse
+			if err := decoder.Decode(&event); err == io.EOF {
+				break
+			} else if err != nil {
+				t.Fatal(err)
+			}
+			events = append(events, event)
+			if event.Done {
+				break
+			}
+		}
+
+		if len(events) < 2 {
+			t.Fatalf("expected at least two streaming events, got %d", len(events))
+		}
+
+		first := events[0]
+		if first.Message.Thinking != "I am thinking through this problem. " {
+			t.Errorf("expected first event thinking %q, got %q", "I am thinking through this problem. ", first.Message.Thinking)
+		}
+
+		if first.Message.Content != "" {
+			t.Errorf("expected first event content to be empty, got %q", first.Message.Content)
+		}
+
+		if first.Done {
+			t.Error("expected first event to be non-terminal")
+		}
+
+		last := events[len(events)-1]
+		if last.Message.Thinking != "" {
+			t.Errorf("expected final event thinking to be empty, got %q", last.Message.Thinking)
+		}
+
+		if last.Message.Content != `{"answer":"42"}` {
+			t.Errorf("expected final event content %q, got %q", `{"answer":"42"}`, last.Message.Content)
+		}
+
+		if !last.Done {
+			t.Error("expected final event to be done")
+		}
+
+		if last.DoneReason != "stop" {
+			t.Errorf("expected final done reason stop, got %s", last.DoneReason)
+		}
+	})
 }

server/sched.go

@@ -21,6 +21,7 @@ import (
 	"github.com/ollama/ollama/format"
 	"github.com/ollama/ollama/fs/ggml"
 	"github.com/ollama/ollama/llm"
+	"github.com/ollama/ollama/logutil"
 	"github.com/ollama/ollama/ml"
 	"github.com/ollama/ollama/types/model"
 )
@@ -229,8 +230,9 @@ func (s *Scheduler) processPending(ctx context.Context) {
 				}
 
 				if runnerToExpire == nil {
-					// Shouildn't happen
-					slog.Error("runner to expire was nil!")
+					// While we were performing load calculations, the loaded runner(s) unloaded in parallel
+					// so findRunnerToUnload returned no runners.  We'll try again and the loadedCount should be zero
+					slog.Debug("runner to expire was nil, retrying")
 					continue
 				}
 				// Trigger an expiration to unload once it's done
@@ -644,27 +646,35 @@ func (s *Scheduler) waitForVRAMRecovery(runner *runnerRef, runners []discover.Fi
 		totalMemoryBefore += gpu.TotalMemory
 		freeMemoryBefore += gpu.FreeMemory
 	}
+	totalMemoryNow := totalMemoryBefore
+	freeMemoryNow := freeMemoryBefore
+
 	go func() {
-		expiresAt := start.Add(5 * time.Second) // typical convergence is 0.5-1.5s
+		// typical convergence is 0.5-1.5s - If it takes more than 5 seconds to discover and converge, let the scheduler estimate VRAM usage
+		ctx, cancel := context.WithTimeout(context.Background(), 5*time.Second)
+		defer cancel()
 		ticker := time.NewTicker(250 * time.Millisecond)
 		defer ticker.Stop()
 		for {
-			<-ticker.C
-			if time.Now().After(expiresAt) {
-				slog.Warn("gpu VRAM usage didn't recover within timeout", "seconds", time.Since(start).Seconds(), "runner", runner)
-				finished <- struct{}{}
-			}
-
-			// Query GPUs, look for free to go back up
-			gpusNow := s.getGpuFn(context.Background(), runners)
-			var totalMemoryNow, freeMemoryNow uint64
-			for _, gpu := range gpusNow {
-				totalMemoryNow += gpu.TotalMemory
-				freeMemoryNow += gpu.FreeMemory
-			}
-			// If we're within ~80% of the estimated memory usage recovered, bail out
-			if float32(freeMemoryNow-freeMemoryBefore) > float32(runner.vramSize)*0.8 {
-				slog.Debug(fmt.Sprintf("gpu VRAM free memory converged after %0.2f seconds", time.Since(start).Seconds()), "runner", runner)
+			select {
+			case <-ticker.C:
+				// Query GPUs, look for free to go back up
+				gpusNow := s.getGpuFn(ctx, runners)
+				totalMemoryNow = 0
+				freeMemoryNow = 0
+				for _, gpu := range gpusNow {
+					totalMemoryNow += gpu.TotalMemory
+					freeMemoryNow += gpu.FreeMemory
+				}
+				logutil.Trace("gpu VRAM convergence", "percent", int(max(float32(freeMemoryNow-freeMemoryBefore), 0.0)/float32(runner.vramSize)*100))
+				// If we're within ~75% of the estimated memory usage recovered, bail out
+				if float32(freeMemoryNow-freeMemoryBefore) > float32(runner.vramSize)*0.75 {
+					slog.Debug(fmt.Sprintf("gpu VRAM free memory converged after %0.2f seconds", time.Since(start).Seconds()), "free_before", format.HumanBytes2(freeMemoryBefore), "free_now", format.HumanBytes2(freeMemoryNow), "runner", runner)
+					finished <- struct{}{}
+					return
+				}
+			case <-ctx.Done():
+				slog.Debug("gpu VRAM usage didn't recover within timeout", "seconds", time.Since(start).Seconds(), "free_before", format.HumanBytes2(freeMemoryBefore), "free_now", format.HumanBytes2(freeMemoryNow), "runner", runner)
 				finished <- struct{}{}
 				return
 			}