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Daniel Han
@danielhanchen
Building @UnslothAI • Making open-source LLMs faster, better & more accessible • YC S24 • ex-NVIDIA ML
Joined April 2016
2K Following    37.2K Followers
We made Unsloth UD3 MiniMax-M3.1-Flash quants! We tested across multiple domains to ensure our quants work great for them as well! By default, MiniMax-M3.1-Flash uses NVFP4 for MoE layers and BF16 / MXFP8 for the rest. UD-IQ1_M retains ~89.9% top-1%. Works in Unsloth Desktop!
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MiniMax-M3.1-Flash can now run locally! We made 2-bit GGUF retain 91.5% top 1 accuracy while being 45% smaller. Run on 150GB RAM. MiniMax-M3.1-Flash is the strongest open model for its size & among the best overall. GGUF: Guide:
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