onnxruntime-ep-mlx

MLX-native ONNX Runtime execution provider for Apple Silicon. It is an out-of-tree plugin EP for ONNX Runtime 1.29 and requires no ONNX Runtime fork.

The wheel bundles MLX 0.32.1 and mlx-c 0.6.0_4. 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 on Apple Silicon and an ONNX Runtime 1.29 build.

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