Prism ML squeezes Qwen 27B from 60GB to 6GB with 1.5-bit quantization, runs on Raspberry Pi
rohanpaul_ai · x · 2026-10-08
On Tom Bilyeu's podcast, Emad Mostaque highlighted an extreme quantization result: Alibaba's Qwen 27B normally needs about 60GB of memory, but a team at Prism ML cut that to 6GB by storing numbers at 1.5 bits instead of 16, while keeping 95% of performance.
- At 6GB the model runs on a Raspberry Pi, which draws about as much power as a human brain.
- Mostaque argued AI models have "pretty much reached the efficiency of a human brain." Full video on Tom Bilyeu's YouTube channel.
Related event: 1.5-bit quantization shrinks Qwen 27B to run on a Raspberry Pi(3 posts)→
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