* create: add server-side MLX imports and drop GGUF conversion
Support safetensors imports through the MLX create pipeline both locally and on the server, including remote upload/staging, draft layer handling, cancellation propagation, transfer limits, and shared manifest/blob writing.
Limit GGUF create to wrapping existing GGUF inputs into Ollama manifests. Remove the in-tree safetensors-to-GGUF converter, server quantization path, and converter-only dependencies so GGUF conversion and quantization stay in llama.cpp tooling.
Keep the MLX path focused on supported safetensors model creation with validation before MLX work, and expose that flow without the --experimental CLI gate.
* address comments
* add client side gguf create fast path
* address comments
* rebase adjustments
* Report cached prompt tokens
Add prompt_eval_cached_count to native responses and expose equivalent cached-token fields through the OpenAI- and Anthropic-compatible APIs. Keep prompt_eval_count as the logical input total while excluding cache hits from CLI and benchmark prefill rates. Surface processed and cached prompt counts in benchmark output.
Collect cache counts from llama-server and MLX, preserve coherent metrics across two-pass structured generation.
Fixes#8008
Related to #15758
* review comments
* fix(docs): correct typos found during code review
Non-functional changes only:
- Fixed minor spelling mistakes in comments
- Corrected typos in user-facing strings
- No variables, logic, or functional code was modified.
Signed-off-by: Marcel Petrick <mail@marcelpetrick.it>
* fix additional typos and shell-unsafe example in docs
---------
Co-authored-by: Patrick Devine <patrick@ollama.com>
Request options are the model's published parameters and the request's
own options layered over the server defaults, so the default
repeat_penalty of 1.1 reaches every model whose parameters leave it
unset. No maker of the library's current models recommends 1.1: their
generation configs either omit the penalty, meaning 1.0, or pin 1.05.
llama.cpp dropped the same 1.1 default in 2024; vLLM, SGLang, and
transformers apply no penalty. An always-on penalty also distorts
output that legitimately repeats tokens, such as code, JSON, and long
reasoning traces.
The penalty is especially costly for speculative decoding, where
drafts are proposed without it: the penalized target rejects drafted
tokens and the depth controller backs off. On muse-glimmer 30B (DFlash
on M5 Max, HumanEval) the 1.1 default costs 13-16% of end-to-end
throughput at greedy and temperature 1 alike, and drops prose
acceptance at temperature 0.8 from 0.44 to 0.30. On qwen3.6-35B it
cuts the mean accepted draft length from 4.3 to 3.5 tokens and makes
the controller stop speculating on prose.
Defaulting to 1.0 disables the penalty unless a model's parameters or
the request set one. Across the library:
- qwen3, qwen3.6, and qwen3-coder pin their own values (1.0, 1.0, and
Qwen's recommended 1.05) and are unchanged.
- Everything else local now matches its maker's no-penalty
recommendation, including gemma2 through gemma4, muse-glimmer, both
laguna 2.1 models, qwen3.5 (previously 1.1 stacked on its
presence_penalty of 1.5), gpt-oss, deepseek-r1 and v3.1, the
nemotron family, granite4, the mistral and llama3/llama4 families,
phi4, glm4, llava, and devstral.
- qwen2.5 recommends 1.05 but ships no parameters, so it moves from
1.1 to 1.0 and still needs a parameters layer to conform.
- Cloud models (kimi-k3, deepseek-v4-flash) never receive these
defaults.
Small older models may repeat themselves more without the penalty
masking it; the remedy is a per-model parameter, not a penalty applied
to every model.
Remove the x/imagegen tree (MLX image generation engine, Flux2/zimage
models, cache, C bindings) and all imagegen integration points:
- server: drop imagegen routes, scheduling, and generate handling
- api/cmd/docs: remove image generation API surface and docs
- middleware/openai: remove image endpoint support
- integration: remove imagegen test suites
- x/create: adopt the rewritten create pipeline from main; drop
imagegen create path (CreateImageGenModel, IsTensorModelDir,
model_index.json detection, Flux2KleinPipeline vision hack)
- retain x/imagegen/manifest (Ollama-store safetensors manifest
loader), still used by x/mlxrunner and x/create/client
- fix Windows MLX dl.dll install, MLX CMake version path, and the
show command after removing safetensors models
Recent upstream Pascal kernel fixes let us compile native SM60/SM61 kernels again instead of relying on PTX JIT, so allow Flash Attention auto at runtime for CC 6.x devices.
Fixes#16591Fixes#16754
The presets and docs had fallen out of sync with what our current ROCm versions on Linux and Windows actually support. We rely on Vulkan now to cover these older unsupported devices.
Our cuda_v12 build requires nvcc fatbin compression, which in turn requires driver 550 or newer. This change filters incompatible CUDA devices based on the runtime and driver version. This allows users to build from source with older toolkits to support older drivers.
Fixes#16449
* broad lint fixes to sidestep CI scope glitch
* runner: Remove CGO engines, use llama-server exclusively for GGML models
Remove the vendored GGML and llama.cpp backend, CGO runner, Go model
implementations, and sample. llama-server (built from upstream llama.cpp via
FetchContent) is now the sole inference engine for GGUF-based models.
(Safetensor based models continue to run on the new MLX engine.) This allows
us to more rapidly pick up new capabilities and fixes from llama.cpp as they
come out.
On windows this now requires recent AMD driver versions to support ROCm v7 as
llama.cpp currently does not support building against v6.
* llama/compat: load Ollama-format GGUFs in llama-server
Squashed from upstream/jmorganca/llama-compat on 2026-04-29.
Source tip: 0c33775d37.
Original source commits:
- 25223160d llama/compat: add in-memory shim so llama-server can load Ollama-format GGUFs
- 7449b539a llm,server: route Ollama-format gemma3 blobs through llama/compat
- 436f2e2b1 llama/compat: make patch-apply idempotent
- 8c2c9d4c8 llama/compat: extend gemma3 handler to cover 1B and 270M blobs
- 021389f7b llama/compat: shrink clip.cpp injection from 18 lines to 1
- 61b367ec2 llama/compat: shrink patch to pure call-site hooks (34 -> 20 lines)
- 36049361c llama/compat: simplify shim (gemma3-tested)
- 8fa664865 llama/compat: add qwen35moe text handler
- db0c74530 llama/compat: add qwen35moe vision (clip) support
- 2a388da77 llama/compat: split shared infra into a util TU
- 9a69a17dc llama/compat: document non-public API dependencies
- d0f38a915 llama/compat: add gpt-oss and lfm2 handlers
- 086071822 llama/compat: add mistral3 text handler (vision TODO)
- 63bde9ff7 llama/compat: add mistral3 vision (clip) support
- 3a57b89d5 llama/compat: apply LLaMA RoPE permute to mistral3 vision Q/K
- 99cb87439 llama/compat: add qwen35, gemma4, deepseek-ocr handlers
- 2c7850dba llama/compat: add nemotron_h_moe handler (latent FFN + MTP skip)
- 9e3b54225 llama/compat: add llama4 text + clip handlers
- 034fee349 llama/compat: add gemma4 clip handler (gemma4v projector)
- 9945c5a93 server: remove dhiltgen/* compat redirect table
- 5d4539101 llama/compat: rewrite gemma4 tokenizer model to BPE
- 7e0765327 llama/compat: add glm-ocr text handler + text-loader load-op hook
- f1bd1a25a llama/compat: add glm-ocr clip handler (glm4v projector)
- 4b5cf3420 llama/compat: collapse text-loader hook back to one new patch line
- eb4ecf4fc llama/compat: extend gemma4 clip handler to gemma4a (audio)
- a23a5e76f llama/compat: fix gemma4a per-block norm tensor mapping
- cd2dcaff4 llama/compat: add embeddinggemma handler
- 1ce8a6b26 llama/compat: add qwen3-vl + qwen2.5-vl handlers
- fd98ffa1e llama/compat: add gemma3n + glm4moelite handlers
- cc7bdf0bc llama/compat: handle null buft in maybe_load_tensor
- 0c33775d3 llama/compat: disable mmap when load_op transforms text-side tensors
* refine implementation
* ci: fix windows MLX build
* ci: fix windows llama-server build
* ci: fix windows rocm build
* ci: windows mlx tuning
Shorten long-tail on build, and get OllamaSetup.exe back under 2g limit
* ci: fix windows dependencies
* win: fix dependency gathering
* disable openmp
* win: arm64 cross-compile build
also DRY out CI steps
* scheduler improvements
* ci: improvements from #15982
* win: favor ninja for faster developer builds
* win: fix build
* win: fix arm64 cross-compile
* win: avoid spaces in compiler path
* misc discovery fixes, and bos handling
* lint fixes
* win: fix arm cross-compile build/CI bugs
* llama.cpp update
* win: handle multiple CRT dirs
* vulkan: add windows iGPU detection
* fix creation bugs for patched models, other refactoring work
* tune batch size for better performance
* ci and lint fixes
* fix repeat_last_n bug
* build: revamp build for better developer UX
* amd, sampler, qwen3next fixes
* version bump
* fix mlx build
* revamp GPU discovery
Scanning the output of llama-server is turning out to be too error prone across
llama.cpp updates, so this switches to a thin dynamic library load against the
bundled GGML libraries so more details can be gathered from the API.
* version bump
* missing file
* ci: fix cache miss on rocm build
* refine vulkan dep handling
* fix ps reporting bug on full GPU load
* improve cmake wiring for customized local builds
* version bump
* docker build arg cleanup
* improve windows exit error logs
* fix community gemma4 support and ci flakes
* fix mlx unit test
* tighten up ps logic to avoid double counting fit log lines
* version bump
* fix ps view for full gpu layer offload
* add MTP wiring for llama-server and create with GGUFs
* pick best template by capabilities
* version bump
* ci: harden apt repos
* remove unused cpu core discovery
* adjust batch default logic to reduce OOMs
* support larger tool calls
* fix audio support, template show
* qwen35 mtp patch support
* flesh out dtypes
* rocm deps
* version bump
* lint fix
* block broken gfx1150 on windows
* fix qwen3.5 moe mtp tensors in patch
* mmproj oom fallback and vulkan on by default
* qwen MTP compat fix
* version bump
* ci: fix WoA cross-compile
* ci: workaround ui tool in cross-compile
* version bump
* win: enable OpenMP for CPU builds
* build: improve developer UX
* ci: windows path workaround for CPU build
* win: fix WoA dependencies
* win: fix large offset reads for mmproj patched loads
* version bump
* fix vulkan dup detection
* add OLLAMA_IGPU_ENABLE and largely disable iGPUs by default
* opt-in MTP, win large offset, integraton fixes
* fix unit test scheduler interaction hang
* fix multi-gpu filtering
* version bump
* review comments
* fix thinking level
* fix linux rocm ordering and granite 3.3 template
* version bump
* ci fix - non-shallow MLX checkout
* bypass linux sysfs unit test on windows
---------
Co-authored-by: jmorganca <jmorganca@gmail.com>
* mlx: add laguna model support
* convert: support fp8 safetensors import
Decode HF F8_E4M3 safetensors with block scale companions into GGUF-supported tensor types, and record which output tensors came from FP8 source weights.
Use that source-precision metadata during create quantization: default FP8-sourced GGUFs to Q8_0, keep non-FP8 tensors at their original precision for Q8_0, and promote non-FP8 quantizable tensors to Q8_0 for Q4_K requests.
* ggml: add laguna model support
* server: preserve generate logprobs with builtin parsers
Generate requests were dropping logprob-only chunks whenever a builtin parser buffered visible content. Chat already handled this case, but generate only forwarded chunks with visible response, thinking, or tool-call output.
Keep generate chunks that carry logprobs even when the builtin parser has not flushed visible content yet, and add a regression test that exercises the behavior with a generic thinking parser.
* review comments - perf improvements
* ggml: implement nemotron 3 nano omni
* add poolside integration
* update poolside doc
* adapt to new cache setup
* fix test
* fix test
---------
Co-authored-by: Eva Ho <hoyyeva@gmail.com>
Parth Sareen