* Deduplicate MLX CUDA runtime payloads
Move CUDA libraries shared by the GGML and MLX backends into the sibling CUDA payload, and teach in-process and subprocess MLX loading to resolve that packaged dependency directory.
Keep MLX-private libraries and JIT headers in the MLX overlay, include the full OpenBLAS Fortran runtime closure, and verify those dependencies in release packaging.
* address comments
* ci: shorten Windows Vulkan build path
Keep the nested shader-generator compiler probes below Windows path limits in checkouts with longer repository names.
* mlx: fix Nemotron bugs and support global scales
Accept published Nemotron layer names while retaining legacy aliases, and
fix layer-count inference and detached MTP quantization. Stabilize Mamba
softplus, preserve FP32 vision normalization, and compile Mamba gate and
norm scaling.
Support per-expert F32 global scales and preserve activation-scale
companions in ModelOpt and compressed-tensors NVFP4 imports. Normalize
reciprocal globals and reject invalid scales. Keep activation scales
separate from weight-only inference.
* mlx: add Nemotron 3.5 Super
* minor adjustments
Move the ollama_xgrammar target into mlxrunner/xgrammar/native so it
can be configured on its own against an installed xgrammar. cmake/mlx
now adds it as a subdirectory and still uses the pinned xgrammar.
Serialize final release jobs and delete old assets before retagging to
avoid overlapping updates and mixed-version payloads.
Keep uploads parallel and retry failures twice with 15s/30s delays.
Retry cleanup using a fresh asset list and upload the checksum manifest
only after all payloads succeed.
The MLX runner is the only Go inference runner left and is no longer
experimental, so its packages leave x/. The bindings become a top-level
mlx package beside the carried patches in mlx/compat, mirroring how
llama/ holds the llama.cpp integration, and the runner becomes mlxrunner
with the architectures nested under the package they implement.
Subpackages move with their parent unless listed.
x/mlxrunner/mlx mlx
x/internal/mlxthread mlx/mlxthread
x/internal/mlxthreadtest mlx/mlxthread/mlxthreadtest
x/internal/mlxtest mlx/mlxtest
x/quant mlx/quant
mlx/compat/*.patch mlx/compat/mlx-c (MLX patches go in mlx/compat/mlx)
x/mlxrunner mlxrunner
x/models/nn mlxrunner/nn
x/models/<arch> mlxrunner/model/<arch>
x/mlxrunner/imports.go mlxrunner/model/architectures (new package)
x/create create
x/safetensors fs/safetensors
x/tokenizer mlxrunner/tokenizer
Every package keeps its name, so the Go changes are the import path
rewrites the moves force, and the CMake, Dockerfile, CI cache keys, drift
check and Darwin payload script follow the new paths. Four edits are not
paths: the runner's blank architecture imports become the package
mlxrunner/model/architectures, so the list to extend for a new model sits
beside the architecture directories; a depguard rule keeps the two test
harnesses out of non-test code, as the x/internal placement used to; the
CI change filter's two entries for the long-deleted x/imagegen/mlx now
name the bindings' CMake project and the carried patches, so a change to
either builds the payload; and the tokenizer parity test reads its
fixtures from its own testdata instead of walking out of x/.
x/server and x/imagegen/manifest stay for the next two commits.
Several pieces outlived the code that used them. The root tokenizer
package implemented the GGUF-side vocabularies for the Go engine and the
safetensors-to-GGUF converter; nothing has imported it since the
converter went. ml/backend.go held the Go engine's Backend, Context and
Tensor interfaces, with fs.Config existing only to be returned from them,
and a single CUDA template instance under ml/backend/ggml survived the
engine removal along with the gitattributes entries for that tree and the
CI change-filter globs for it and for the long-gone llama/llama.cpp. From
the image generation engine, an integration test group that no test
registers, its build tag, and the StepBar progress widget remained.
DeviceInfo.IsBetter has no caller at all.
All of it goes. Tidying the module file drops the regexp2 dependency and
leaves protobuf as an indirect requirement. The llama3.2 tokenizer
fixtures stay: the MLX runner's tokenizer uses them for its GGML parity
test.
Includes quantized matmul corruption fix, which impacts nvfp4 multimodal models (gemma4 vision towers). Deferring wiring up the new MLX-C thread-local stream/sync APIs for now.
* 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
* ci: rebuild MLX macOS test payloads the release can't supply
The MLX unit test dependency payload can go stale when a PR changes the
xgrammar wrapper (release dylib lacks the new symbols) or bumps MLX pins (no
matching release, so MLX tests silently skipped). Compare the matched tag's
build rules and wrapper sources against the checkout, rebuilding only
libollama_xgrammar.dylib on drift; with no matching release, build one Metal
variant at the platform default.
* address comments
* ci: wire up MLX unit tests for PR runs
Download the latest Darwin release payload matching the current MLX and MLX-C revisions so macOS PR tests can exercise MLX without rebuilding it. If no matching release exists after a pin bump, leave MLX tests skipped until the next release.
Add whole-tree race coverage and smoke-run committed benchmarks. Verify generated UI types, and stabilize tests exposed by the broader CI coverage.
* review comments
* mlx: run tests on one pinned worker
Keep MLX tests and benchmarks on a shared pinned thread while preserving Fatal, Skip, and Cleanup semantics. Also clean stale CI payloads and ensure updater workers shut down cleanly.
* addres comments
The MLX runner accepted the API's format field but did not enforce it:
requests asking for JSON or a JSON Schema got unconstrained text, and
clients had no way to tell.
Enforce format with xgrammar: each sampling step masks the logits to
the tokens the grammar allows, so every emitted token and the end of
generation are valid under the constraint. Sampling, penalties, and
logprobs see the constrained distribution, and "json" yields a JSON
object, as the API documents and the llama-server path already
enforces. Only sampling waits on the mask; the forward pass is
dispatched before it, so constrained decoding stays pipelined.
The grammar engine is a dynamic library alongside MLX; when it is
missing, plain inference is unaffected and structured requests fail
with an explicit error. Constrained requests decode without
speculative decoding for now.
Decoding 256 tokens of a book-list schema on qwen3.8:27b-mlx (M5 Max,
seed 42, thinking off); pre-decode is the request time spent before
the first token:
unconstrained ~65 tok/s pre-decode ~70 ms
unconstrained, no draft ~32 tok/s pre-decode ~70 ms
JSON schema ~32 tok/s pre-decode ~70 ms
Schema and draft-less decoding are equal to within 0.1 tok/s in
paired adjacent requests, and a cold grammar compile adds nothing
measurable to pre-decode. The gap to unconstrained decoding is the
disabled draft model.
Fixes#16563
Co-authored-by: Daniel Hiltgen <daniel@ollama.com>
* glimmer: implement the Muse Glimmer model
MLX model (language + vision encoder) with DFlash draft wiring, llama-server DFlash support and rope-interleave fix, renderer and parser, tokenizer fixes, and the import quantization policy.
* mlxrunner: report committed prefill chunks after the sweep and eval
The drafter's flush evaluates its report, and an eval that runs while the chunk's construction handles are still live cannot free any intermediate buffer. On media chunks that retention keeps the whole vision tower resident and grinds the Metal allocator at its limit until the request dies. Pin the report's inputs across the sweep, report after the chunk materializes, and release media items after the report so a drafter can still capture the rows its deferred flush embeds.
* ci: retry CUDA pre-release download
golangci-lint ran with only-new-issues, which filters findings down to the
lines a PR adds. That silently drops any issue a diff introduces at a
distance, where the report anchors to a line the diff never touched.
CI now is enabled to scan all files. This PR also fixes the last few
straggler lint glitches outside of integration, which I'll tackle
in a follow up PR.
If we have one flake, don't stop other jobs that will most likely work so when
we re-run failed jobs, only the flake and dependents need to be run. This should
help reduce the time it takes to get past a flake and finish a release build.
* llama-server followups
Misc fixes for #16031
- Add back dropped ROCm build flag for multi-GPU support on windows
- Fix amdhip64_*.dll version detection for "latest" selection
- Fix embeddings API for consistent normalize behavior with prior versions
* ci: set up for automated llama.cpp update testing
* reduce batch for fa-disabled, and constrained vram
* mlx: fix v3 load bug on m5
Imagegen was incorrectly loading v3 first. This DRYs out the loading code so imagegen gets the same new v4/v3 selection logic.
* fix reload bug on embedding models
* bump version
* steer user how to enable iGPU when disabled
* 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>
* ci: speed up release builds
This should help speed things up for release. It also will help
speed up local developer builds a little.
* ci: dedup linux build steps and optimize
* review comments
* app: harden update flows
This hardens the windows update flows and adds a new opt-in and CI triggered unit test to verify Mac/Windows updates with verification.
* test: harden unit tests for OLLAMA_MODELS being set
* app: harden updater
This change adds support for MTP (multi-token prediction) speculative decoding for the
gemma4 model family.
It includes:
* support for importing safetensors based gemma4 draft models with `ollama create`
* a new DRAFT command in the Modelfile for specifying draft models
* a --quantize-draft flag for the ollama create command to quantize the draft model
* cache support for speculation
* changes to the rotating cache to be able to handle MTP correctly
* sampling support for draft model token prediction
---------
Co-authored-by: Daniel Hiltgen <daniel@ollama.com>
* mlx: Improve M5 performance with NAX
This modifies the Mac release to now have 2 builds of MLX for broader
compatibility while supporting the latest M5 hardware features. NAX requires
building with xcode 26.2 and targetting support only for OS v26 and up. Since
we want to support older MacOS versions as well, we now need 2 different MLX
builds and runtime detection logic to select the optimal version. The newer
build will detect NAX missing at runtime, so it is safe to run on pre M5 macs.
* mac: prevent generate on cross-compiles
For some versions of Xcode, cmake builds are failing due to header problems in
cross-compiling during the generate phase. Since generate is producing arch
independent generated output, we can skip this during cross-compiling.
Use 7z compression (better compression rate) if found in path. That
alone isn't sufficient to get us under 2G, so MLX is now split out as a
discrete download. Fix CI so it will fail if artifacts fail to upload.
* prefer rocm v6 on windows
Avoid building with v7 - more changes are needed
* MLX: add header vendoring and remove go build tag
This switches to using a vendoring approach for the mlx-c headers so that Go
can build without requiring a cmake first. This enables building the new MLX
based code by default. Every time cmake runs, the headers are refreshed, so we
can easily keep them in sync when we bump mlx versions. Basic Windows
and Linux support are verified.
* ci: harden for flaky choco repo servers
CI sometimes fails due to choco not actually installing cache. Since it just speeds up the build, we can proceed without.
* review comments
This adds a new powershell install script suitable for running via
irm https://ollama.com/install.ps1 | iex
If you download the script and run '-?' it reports basic usage
information, as well as usage examples for common customization
options. The script is signed as part of the release process
to ensure it can run on a typically configured Windows system.
This does not include doc updates - we can merge those after a release
ships to avoid user confusion.
Allow installing Ollama on MacOS directly from the command line. This is in line with other CLI tools and results in a more streamlined experience when the user is looking to use the CLI specifically.
With the upcoming addition of MLX, the linux bundle will exceed the
maximum github artifact size of 2G. This change will bring the size
back down.
The install.sh changes support backwards compatibility for prior versions
thus should be safe to merge concurrently with this change.
Daniel HiltgenandGitHub
Jeffrey Morgan
Daniel Hiltgen
Jesse Gross
Parth SareenandGitHub
Bruce MacDonaldandGitHub
WhatToPutHereandGitHub