
MiniMax M2.7
Self-evolving agentic MoE with 230B parameters and 10B active per token, open weights.
About
MiniMax M2.7 launched March 18, 2026 as the point release of the M2 series. It is a sparse mixture-of-experts model with about 230B total parameters and roughly 10B active per token, with a 200K-token context window. MiniMax says an internal version ran over 100 autonomous rounds of scaffold self-optimization, improving about 30% with no human in the loop.
The weights were released on Hugging Face under a modified MIT license whose commercial-use restriction drew community criticism; it is open-weights but not open-source. It scores 56.22% on SWE-Pro and 57.0% on Terminal Bench 2, placing it near closed frontier models on agentic coding tasks.
Specs
Context window
Pricing
Free quota
API access
Weights
Released
Benchmarks
Provider-reported unless a source says otherwise. Benchmarks are marketing-adjacent by nature — treat them as directional.
Use cases
Trust score — 8/10
Scored 8/10 (verified tier, metrics-v1). Evidence: Verified via vendor site/docs/GitHub and reputable coverage, wave 105; Trending score 84/100 from researcher assessment.