antirez Ports MiniMax H3 to Metal

Salvatore Sanfilippo — the author of Redis — published a native C+Metal inference engine for MiniMax H3 targeting M3/M5 Macs, roughly repeating what llama.cpp did for language models: bypass the Python stack, write tight hardware-specific kernels, and find out how fast the silicon can actually go.

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When the Sandbox Shares the GPU's Memory

A blog post published April 18 describes a technique for running LLM inference inside a WebAssembly sandbox at near-native GPU speed on Apple Silicon. By overriding Wasmtime's memory allocator to back Wasm linear memory with a Metal buffer via makeBuffer(bytesNoCopy:), the author collapses the Wasm–GPU boundary entirely: 0.03 MB overhead vs 16.78 MB for the copy approach, ~9 ms/token for Llama 3.2 1B on M1, and KV cache snapshots that restore 5.45× faster than recomputing prefill.

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