MiniMax‑M1
Overview
Open‑source large‑scale reasoning model with 1 million token context and hybrid Mixture‑of‑Experts architecture.
Best For Professions:
MiniMax‑M1 is an open‑weight, hybrid Mixture‑of‑Experts large language model offering natively a 1 million token context window. It uses lightning attention and efficient RL training (CISPO) to excel at long-context reasoning, tool-use, coding, and mathematics. Released under Apache 2.0, it supports structured function calling and is deployable via vLLM, Transformers, or API.
AI Agent Store research
What the evidence says about MiniMax‑M1
MiniMax‑M1 is best understood as an open-weight reasoning model rather than an agent-development framework. The MiniMax-M1 repository presents an open-weight, large-scale hybrid-attention reasoning model.
Last reviewed July 30, 2026
Verified capabilities
- Agent application development
The MiniMax-M1 repository presents an open-weight, large-scale hybrid-attention reasoning model.[1]
Where it fits best
- Evaluating an open-weight hybrid-attention reasoning model.[1]
Buying and deployment notes
Deployment: Source repository[1]
Sources and research method (1)
We record only claims tied to public sources checked by our team or listing workflow. Counts above are derived directly from this profile, not a subjective rating.
Autonomy level
83%
Comparisons
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Some of the use cases of MiniMax‑M1:
- Processing extremely long documents or codebases in a single pass
- Building AI agents with tool-use and function-calling
- Advanced mathematical and coding reasoning
- Deploying open-source LLMs with efficient inference
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Popularity level: 73%
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