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
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Co-authored-by: Daniel Hiltgen <daniel@ollama.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
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Co-authored-by: Eva Ho <hoyyeva@gmail.com>
* mlx: Support NVIDIA TensorRT Model Optimizer import
* x/create: support FP8 safetensors import
Decode HF F8_E4M3 safetensors with block scale companions into MLX-importable tensor blobs, including compressed-tensors weight_scale metadata, packed NVFP4 layouts, and mixed-precision tensor headers.
Use that source-precision metadata during create quantization: default FP8-sourced imports to mxfp8, allow source FP8 to target MLX low-bit formats, preserve source-quantized NVFP4 layouts, selectively keep or promote tensors based on their source precision, and detect quantized dtype from mixed-precision safetensors manifests.
* review comments
* gemma4: implement Gemma 4 model for MLX (text-only runtime)
* gemma4: two MoE + SWA prefill perf fixes
Two performance optimizations in the gemma4 forward pass
1. Memoize the sliding-window prefill mask across layers.
2. Softmax only over the selected experts in Router.Forward.
* review comments
* mlx: add op wrappers for Conv2d, Pad, activations, trig, and masked SDPA
Add Conv2d, flexible Pad (with axes/mode), PadConstant, Maximum,
Minimum, Softplus, ReLU, GLU, Clamp, Sin, Cos, Clip,
ScaledDotProductAttentionMasked, and RoPEWithFreqs. Refactor
RoPEWithBase to delegate to RoPEWithFreqs.
* review comments
* mlx: fix ScaledDotProductAttentionMasked to consult the mask argument
Improve the MLX model creation pipeline with several model-agnostic changes:
- Rewrite supportsVision to use vision_config instead of architecture name
- Add supportsAudio for audio encoder detection
- Add alignment checking (isAligned) for quantization group sizes
- Support per-projection mixed quantization in MoE expert packing
- Record per-tensor quant metadata in safetensors blobs
- Parse per-tensor quant metadata at model load time
- Validate quantize output is non-empty before storing
- Fix pin/unpin cleanup in expert group quantization
- Promote v_proj/k_proj/down_proj to INT8 for INT4 base quant
- Add MetalIsAvailable() utility
- Skip audio encoder tensors from quantization
* create: Clean up experimental paths
This cleans up the experimental features, and adds both unit and integration test coverage to verify no regressions.
* create: preserve config and layer names when creating from safetensors models
When creating a model FROM an existing safetensors model, ModelFormat,
Capabilities, and layer Name fields were lost. ModelFormat stayed empty
because it's only set from GGML layers (which safetensors models lack),
and layer names weren't copied in parseFromModel. This caused derived
models to fail loading ("config.json not found in manifest").
* review comments
This change adds a tensorImportTransform interface for model-specific
tensor transformations during safetensors import. This allows importing
and modifying the standard HF based weights as well as the mlx-community
derived pre-quantized safetensors repos to be directly
imported into `ollama create`. Right now this only works with Qwen3.5
importing which does tensor renaming, norm weight shifting (it
adds +1 to each value of the norm vectors), conv1d transposition,
and casts to BF16s for F32 based vectors.
* 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 change adds support for qwen3.5-next-moe models (qwen3-next/qwen3.5-next/qwen3-coder) to the MLX runner. It also:
* introduces recurrent cache support and related MLX ops
* updates pipeline/runner integration and adds tests
* properly quantizes stacked expert tensors
* a Gated Delta Metal kernel for fast SSM inference
* adds new MLX calls for Conv1d, DepthwideConv1d, Contiguous, Exp, Log, SoftmaxAxis
This change includes:
- changes to the safetensors metadata format
- changes to the create command to properly create the blobs with the new format
- changes to load the new format
- fixes ollama show to properly show each tensor
- Fix panic in ollama show for image gen models (safe type assertion)
- Add vision capability for Flux2KleinPipeline models at create time
- Flatten transparent PNG images onto white background for better results
Add --quantize fp4 support to ollama create for image generation models
(flux2, z-image-turbo), using MLX's affine 4-bit quantization.
Changes:
- Add fp4 to validation in CreateImageGenModel
- Add FP4 case to quantizeTensor (group_size=32, bits=4, affine mode)
- Add GetQuantization() to WeightSource interface for dynamic params
- Update LoadLinearLayer to use quantization params from model metadata
* x: make `ollama create --experimental` import from safetensors
This change allows pulling in safetensors models into the new experimental model format, and also
fixes the `ollama show` command to be able to correctly display the model information.
* gofumpt the linter
* gofumpt the linter again
* validate the model name
