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MiniMax发布推理模型对标DeepSeek,算力成本仅约53万美元

Core Insights - MiniMax, one of the "Six Little Dragons," has announced significant updates, starting with the release of its first open-source inference model, MiniMax-M1 [1] - MiniMax-M1 has shown competitive performance in benchmark tests, comparable to leading overseas models like DeepSeek-R1 and Qwen3 [3] - The model's training was completed in just three weeks using 512 H800 GPUs, with a total computing cost of only $534,700, which is an order of magnitude lower than initially expected [3][8] Performance Metrics - MiniMax-M1's context window length is 1 million tokens, which is eight times that of DeepSeek R1 and matches Google's Gemini 2.5 Pro, allowing superior performance in long-context understanding tasks [5] - In the TAU-bench evaluation, MiniMax-M1 outperformed DeepSeek-R1-0528 and Google's Gemini 2.5 Pro, ranking just below OpenAI o3 and Claude 4 Opus globally [7] - The model excels in coding capabilities, significantly surpassing most open-source models, with only a slight gap behind the latest DeepSeek R1 [7] Innovations and Cost Efficiency - MiniMax-M1 utilizes a hybrid architecture based on a lightning attention mechanism, enhancing efficiency in long-text input and deep reasoning tasks [7] - The introduction of the CISPO reinforcement learning algorithm has resulted in faster convergence performance compared to Byte's recent DAPO algorithm, contributing to the low training cost [8] - MiniMax's pricing strategy is tiered based on input length, with costs ranging from $0.8 to $2.4 per million tokens for input and $8 to $24 for output, offering competitive pricing against DeepSeek [8] Competitive Landscape - Concurrently, another competitor, Moonlight, has released its programming model Kimi-Dev-72B, which reportedly achieved the highest open-source model level in SWE-bench tests, surpassing the new DeepSeek-R1 [8] - However, Kimi-Dev-72B faced scrutiny for potential overfitting, as it generated less code than required for certain tasks, raising questions about its performance reliability [9] - The AI industry is witnessing renewed competition among the "Six Little Dragons," with MiniMax expected to release further updates in the coming days, potentially impacting the multi-modal AI landscape [9]