onnxruntime-ep-mlx
MLX-native ONNX Runtime execution provider for Apple Silicon. It is an out-of-tree plugin EP for ONNX Runtime 1.31 or newer and requires no ONNX Runtime fork.
The wheel bundles MLX 0.32.2 commit 1f8e74e3 and mlx-c commit c74db530. It supports encoder, LLM
prefill, and token-at-a-time decode workloads, including quantized matmul,
attention, normalization, convolution, shape operations, and compiled
shape-specialized If, Loop, and Scan control flow.
See the complete README for operator coverage, performance results, diagnostics, build instructions, and C/C++ integration.
Install
pip install -U onnxruntime-ep-mlx
import onnxruntime as ort
import onnxruntime_ep_mlx
onnxruntime_ep_mlx.register_execution_provider_library()
session = ort.InferenceSession(
"model.onnx",
providers=["MLXExecutionProvider", "CPUExecutionProvider"],
)
outputs = session.run(None, feeds)
The package requires macOS 14+ on Apple Silicon, Python 3.11+, and ONNX Runtime 1.31 or newer.
The 0.31.x package series targets ABI 31 and is built with ONNX Runtime 1.31 headers.
1 maintainer
Metadata
1 maintainer
Release files for onnxruntime-ep-mlx 0.31.0
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| onnxruntime_ep_mlx-0.31.0-py3-none-macosx_14_0_arm64.whl | Python 3 | none | macOS 14.0+ ARM64 | Details |
Total release size: 43.5 MB
Release files / onnxruntime_ep_mlx-0.31.0.tar.gz
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