摩爾線程宣佈已爲月之暗面開源的2.8萬億參數Kimi K3模型完成適配，基於自研MTT S5000訓推一體卡與MUSA軟件棧，實現極速穩定運行，爲國產算力支撐萬億大模型再添底氣。
國產人工智能算力領域取得重要突破，摩爾線程近日發佈並開源了業內首個基於國產全功能GPU底座的代碼大模型MusaCoder。該模型專門用於GPU底層算子生成，其完整後訓練流程在“誇娥”智算集羣上完成，依託MTT S5000 GPU實現，標誌着國產算力生態邁出關鍵一步。
在第九屆數字中國建設峯會上，中國移動將首次公開展示其自研的“九天”35B通用大模型。摩爾線程宣佈，其旗艦GPU MTT S5000已完成對該模型的全流程適配與推理驗證，這標誌着國產算力生態的重要突破。通過自研MUSA軟件棧和SGLang-MUSA高性能推理引擎，摩爾線程實現了“九天”35B模型推理全鏈路的深度融合與優化。
摩爾線程自主研發的MUSA架構成功適配開源推理框架llama.cpp，支持在MTT S80/S3000/S4000系列GPU上高效運行AI推理。此前MUSA SDK已擴展至Intel和海光平臺，此次適配進一步降低了大模型部署門檻。llama.cpp作爲輕量化跨硬件框架，支持LLaMA、Mistral等模型及多模態應用。這一突破爲國內AI硬件生態注入新活力，推動AI技術在各領域的應用普及。
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musaoc
一個基於HuggingPics生成的輕量級圖像分類模型，用於性別分類任務。
musadac
基於transformers庫的烏爾都語模型，適用於自然語言處理任務。
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