* mlx: update to HEAD on 3/23
Also fixes a few misc vendoring bugs uncovered with this first update.
This also renames the version files to make them clearer.
* CUDA Fast Gated Delta kernel
* mlx: detect eval errors and panic
On model errors or missing kernels, don't mask the error, bubble it up.
The CLI now links to the lazy-load MLX code, but that still happens in
init functions. On internal MLX errors, the CLI exits before it has a
chance to start. This change re-wires the MLX error handling so it
doesn't exit by default. The MLX based runners currently expect exits
on failure, so they re-initialize the default error handling. We can
refine error handling for better go stack traces in the future.
* 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 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
* MLX - dynamic loading of mlx-c
Create a wrapper layer to indirect the dependency on mlx-c so
the main ollama binary does not have a load-time dependency on mlx-c, mlx, and on linux, cuda. Lazy load the library via dlopen
so we can adjust the path to ensure the dependencies are found
and fail gracefully if not present.
* review comments
* fix broken tests
TeaCache:
- Timestep embedding similarity caching for diffusion models
- Polynomial rescaling with configurable thresholds
- Reduces transformer forward passes by ~30-50%
FP8 quantization:
- Support for FP8 quantized models (8-bit weights with scales)
- QuantizedMatmul on Metal, Dequantize on CUDA
- Client-side quantization via ollama create --quantize fp8
Other bug fixes:
- Fix `/api/show` API for image generation models
- Server properly returns model info (architecture, parameters, quantization)
- Memory allocation optimizations
- CLI improvements for image generation
* WIP - MLX backend with gemma3
* MLX: add cmake and go tag build toggles
To build the new MLX backend code:
cmake --preset MLX
cmake --build --preset MLX --parallel
cmake --install build --component MLX
go build -tags mlx .
Note: the main.go entrypoint for the MLX engine will change in a follow up commit.
* add experimental image generation runtime
* add experimental image generation runtime
* MLX: wire up cuda build for linux
* MLX: get dependencies correct and dedup
This is still too large for a unified github artifact, but is now "correct" for the mlx_cuda_v13
directory.
* fix relative link bug in dedup
* Add darwin build and readme
* add go build tag for mlx dependent code and wire up build_darwin.sh
* lint cleanup
* macos: build mlx for x86
This will be CPU only.
* cuda build instructions and fix drift from mlx bump
* stale comment
* Delete agent helper doc
* Clean up readme.md
* Revise README for tokenizer clarity and details
Updated README to clarify tokenizer functionality and removed correctness section.
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Co-authored-by: jmorganca <jmorganca@gmail.com>
