MiniMax M2.5: Opus-Level Performance at $1 per Hour
MiniMax M2.5 achieves SWE-bench 80.2% using only 10B active parameters from a 230B MoE architecture. 1/20th the cost of Claude Opus with comparable coding performance. Forge RL framework, benchmark analysis, pricing comparison.
MiniMax M2.5: Opus-Level Performance for $1 per Hour
On February 12, 2026, Shanghai-based AI startup MiniMax released M2.5. SWE-bench Verified 80.2%, BrowseComp 76.3%, Multi-SWE-Bench 51.3%. All within 0.6%p of Claude Opus 4.6, at 1/20th the price.
The model is available as open weights on Hugging Face under a modified MIT license. It runs on a 230B parameter MoE architecture, activating only 10B at inference time. Running the 100 TPS (tokens per second) Lightning variant continuously for one hour costs about $1.
This post analyzes M2.5's architecture, training methodology, benchmark performance, and pricing structure, and examines what it means for the AI industry.
Architecture: 230B Total, 10B Active
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