Unsloth makes MiniMax-M3.1-Flash runnable locally
Unsloth has released a 2-bit GGUF quantized version of MiniMax-M3.1-Flash, which retains 91.5% top-1 accuracy while reducing size by 45%, and can run on 150GB of memory. Unsloth claims this model is the strongest among open-source models of the same size, and provides a GGUF download link and usage guide. MiniMax officially previously introduced that M3.1 Flash reaches 62% on Automation-Bench, 74% on DeepSWE, and 91% on BabyVision, with API pricing at $0.15/$0.60 per 1M input/output tokens.
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The original text provides the accuracy retention ratio after quantization compression and the memory threshold, so readers can judge the feasibility of local deployment based on these figures.
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View original postMiniMax M3.1 Flash: Space Performance + Bunny Speed 🚀🐰 Yes, Space Bunny - which has topped global leaderboards with 200T+ tokens - was an earlier version of M3.1 Flash. 💰Redefining the performance economics of agentic AI. M3.1 Flash achieves frontier-level intelligence across key tasks such as Cowork (Automation-Bench: 62%; ALE: 30%), Coding (DeepSWE: 74%) and Visual Reasoning (BabyVision: 91%), at 1/3 the cost of M3 and 3x the speed. API pricing (flat rate): $0.15 / $0.60 per 1M input/output tokens, with cache reads at $0.015 / 1M tokens. Model weights will arrive on Oct 23. API: https://t.co/fHRdSV73Hr M Plan: https://t.co/XfJWSyauda MiniMax Code for desktop: https://t.co/SGmLTI2HQm
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MiniMax M3.1 Flash: Space Performance + Bunny Speed 🚀🐰 Yes, Space Bunny - which has topped global leaderboards with 200T+ tokens - was an earlier version of M3.1 Flash. 💰Redefining the performance economics of agentic AI. M3.1 Flash achieves frontier-level intelligence across key tasks such as Cowork (Automation-Bench: 62%; ALE: 30%), Coding (DeepSWE: 74%) and Visual Reasoning (BabyVision: 91%), at 1/3 the cost of M3 and 3x the speed. API pricing (flat rate): $0.15 / $0.60 per 1M input/output tokens, with cache reads at $0.015 / 1M tokens. Model weights will arrive on Oct 23. API: https://t.co/fHRdSV73Hr M Plan: https://t.co/XfJWSyauda MiniMax Code for desktop: https://t.co/SGmLTI2HQm
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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: https://t.co/A8Xp9uqpq1 Guide: https://t.co/gW5gp25niu https://t.co/txl6ZPRTjs