MiniMax-M3.1-Flash推出2位GGUF本地部署版
Unsloth AI与MiniMax表示，Dynamic GGUF量化使428B参数的MiniMax-M3.1-Flash能够本地部署。MiniMax称2位版本占用143.9GB，并在七个领域实现91.5%的top-1 token一致率；Unsloth则称其保留91.5%的top-1准确率、体积缩小45%，可在配备150GB内存的系统上运行。该模型可通过Unsloth Desktop和llama.cpp自托管，并提供面向现有应用和智能体的OpenAI兼容API。
此次发布通过降低本地部署资源需求，扩展了MiniMax-M3.1-Flash的自托管选择，但体积和准确率数据均来自厂商声明。
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://huggingface.co/unsloth/MiniMax-M3.1-Flash-GGUF Guide: https://unsloth.ai/docs/models/minimax-m3.1-flash
MiniMax (official): 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
#MiniMax#Unsloth AI#MiniMax-M3.1-Flash#Unsloth Desktop#llama.cpp