I ran a 7B Mixture-of-Experts LLM in a language I built — token-identical to fp32

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I've been building machin (MFL), a machine-first language, and using it to write an LLM inference engine with zero dependencies — no PyTorch, no llama.cpp, no BLAS, no Python at runtime. Just a static binary. The wall A dense 1B model got me ~20 tok/s on a laptop CPU. That's the ceiling, and it's fundamental: decode speed is set by bytes moved per token, and on weak hardware you're pinned to the memory bus