Expose precompiled_metal_kernel to load offline-compiled .metallib (-Ofast) for custom kernels

[dahai80]

Motivation

mx.fast.metal_kernel compiles Metal source at runtime via MTLDevice::newLibrary(source, options). The runtime compiler does not expose the -O / -ffast-math optimization flags available to the offline xcrun metal compiler. For memory-latency-bound custom kernels (e.g. INT4 GEMV for LLM decode), this limits how aggressively the user's kernel can be optimized relative to MLX's own mlx.metallib (built offline via mlx_build_metallib).

I found that the C++ layer already has the scaffolding for precompiled kernels but it is not wired through:

• CustomKernel in mlx/fast_primitives.h already has an is_precompiled_ field (L529)
• metal_kernel() in mlx/backend/common/metal_kernel.cpp passes is_precompiled=false (L377)
• CustomKernel::eval_gpu in mlx/backend/metal/custom_kernel.cpp silences the field with (void)is_precompiled_; (L17) and always calls d.get_library(name, compile_options, builder) — the JIT path
• Device::get_library(name, path) in mlx/backend/metal/device.cpp (L631) already supports loading a .metallib from a path, and load_library (L251) handles colocated/path-based lookup

So the machinery is 90% present — is_precompiled_ appears to be a designed-but-unimplemented feature.

Proposal

Expose mx.fast.precompiled_metal_kernel(name, input_names, output_names, metallib_path, ...) that:

1. Loads a user-provided .metallib (compiled offline with xcrun -sdk macosx metal -Ofast ...)
2. Looks up the kernel function by the same custom_kernel_<name>_<types> naming convention the JIT path uses

This mirrors the existing mx.fast.precompiled_cuda_kernel (which already exists for the CUDA backend).

Measured impact (M5 Max, MLX 0.32)

INT4 GEMV kernel (same source as MLX's native qmv_fast_impl algorithm), compiled offline with -Ofast vs runtime JIT vs native mx.quantized_matmul. N-op loop (200 ops, 31 trials, paired A/B, median):

K	native	JIT	-Ofast precompiled	-Ofast vs native
20480	1.83ms	1.65ms	1.77ms	-3.6%
28672	2.68ms	2.64ms	2.52ms	-5.9%
32768	2.44ms	2.38ms	2.35ms	-3.9%
40960	5.03ms	4.82ms	4.83ms	-4.0%

• -Ofast precompiled is 7.5% faster than the JIT version at K=20480 (fastMath + offline optimizer)
• At K≥20480 it surpasses native mx.quantized_matmul by 3-6%, confirmed across two independent runs
• Parity maintained (max diff 9e-4 in fp16, same as JIT)
• At K<20480 (8K-16K) the op is launch-overhead-bound and the gap is within noise

The native mlx.metallib is compiled with -fno-fast-math (per cmake/extension.cmake L29). Allowing user kernels to opt into -Ofast (fastMath) gives them an advantage native doesn't have, for ops where the precision tradeoff is acceptable (int4 dequant accumulation is fp32 internally; only the final half cast is affected).

Files to change (rough)

• mlx/backend/common/metal_kernel.cpp: add precompiled_metal_kernel() factory (mirror metal_kernel but pass is_precompiled=true + path as source_)
• mlx/backend/metal/custom_kernel.cpp: when is_precompiled_, call d.get_library(lib_name, source_) (path-based) instead of the builder path
• mlx/fast.h: declare precompiled_metal_kernel()
• python/src/fast.cpp: bind mx.fast.precompiled_metal_kernel

Happy to open a PR if this approach is acceptable.

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