How a 30B model fits on a 32GB GPU: search-based quant plus spec decoding

TimDarcet · x · 2026-10-21

Addressing skepticism that 30B params can't fit a 32GB GPU, TimDarcet explains the team used greedy and evolutionary search to find a custom quantization scheme minimizing both memory footprint and perplexity error, yielding two Pareto-optimal tradeoffs, plus speculative decoding. The Pareto chart shows EvoPress and Greedy-KL beating GPTQ, AWQ and Uniform NVFP4.

Related event: Meta team trains 30B LLM from scratch in months, squeezes it into a 32GB GPU(5 posts)→

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