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MiniMax

MiniMax M2.7-highspeed

MiniMax M2.7-highspeed is an accelerated SOTA model engineered for scenarios demanding extreme efficiency. It perfectly inherits the core intelligence and robust digital workspace capabilities of the standard M2.7. In real-world software engineering, M2.7 excels by independently driving end-to-end project delivery while efficiently handling advanced tasks such as log analysis, bug troubleshooting, code security, and machine learning. In the professional workspace, it boasts the highest open-source GDPval-AA score (1495 ELO). It delivers high-fidelity, complex editing and multi-turn revisions across the Office suite (Excel, PPT, Word), elevating task execution to industry-leading standards. Built for complex environment interactions, M2.7 maintains an impressive 97% skill-following rate even with complex, long-context tool calls (>2000 tokens). Beyond its robust productivity, M2.7 breaks the "cold tool" stereotype of traditional models. With exceptional identity retention and high emotional intelligence (EQ),

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MiniMax M2.7

MiniMax-M2.5 is a SOTA large language model designed for real-world productivity. Trained in a diverse range of complex real-world digital working environments, M2.5 builds upon the coding expertise of M2.1 to extend into general office work, reaching fluency in generating and operating Word, Excel, and Powerpoint files, context switching between diverse software environments, and working across different agent and human teams. Scoring 80.2% on SWE-Bench Verified, 51.3% on Multi-SWE-Bench, and 76.3% on BrowseComp, M2.5 is also more token efficient than previous generations, having been trained to optimize its actions and output through planning.

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MiniMax M2.5-highspeed

MiniMax M2.5-highspeed is an accelerated SOTA model engineered for scenarios demanding extreme efficiency. It perfectly inherits the core intelligence and robust digital workspace capabilities of the standard M2.5—including its 80.2% score on SWE-Bench Verified, seamless manipulation of Office documents, and versatility in cross-software collaboration. With zero compromise on reasoning precision or logical depth, the Highspeed version delivers ultra-low latency inference through rigorous engineering optimization. This means you get more than just an intelligent assistant capable of planning and self-optimization; you gain a "high-velocity engine" that responds to high-frequency calls and processes complex document streams in near real-time, making it ideal for latency-sensitive interactive applications and large-scale automated pipelines.

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MiniMax M2.5

MiniMax M2.1 is a cutting-edge AI model designed to revolutionize how developers build software. With enhanced multi-language programming support, it excels in generating high-quality code across popular languages like Rust, Java, Golang, C++, Kotlin, Objective-C, TypeScript, and JavaScript. Key improvements include: 22% faster response times and 30% lower token consumption for efficient workflows. Seamless integration with leading development frameworks (Claude Code, Droid Factory AI, BlackBox, etc.). Full-stack development capabilities, from mobile (Android/iOS) to web and 3D interactive prototyping. Optimized performance-to-cost ratio, making AI-assisted development more accessible. Whether you're a software engineer, app developer, or tech innovator, M2.1 empowers smarter coding with industry-leading AI.

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Minimax M2.1

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MiniMax M1

MiniMax-M1: The World's First Open-Weight, Large-Scale Hybrid Attention Inference Model MiniMax-M1 adopts a Mixture of Experts (MoE) architecture and integrates the Flash Attention mechanism. The model contains a total of 456 billion parameters, with 45.9 billion parameters activated per token. Natively, the M1 model supports a context length of 1 million tokens—8 times that of DeepSeek R1. Additionally, by combining the CISPO algorithm with an efficient hybrid attention design for reinforcement learning training, MiniMax-M1 achieves industry-leading performance in long-context reasoning and real-world software engineering scenarios.

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