MiniMax-M2.7
Description
MiniMax M2.7 features model self-improvement driving productivity innovation. It builds complex agent harnesses independently to accomplish highly complex productivity tasks. M2.7 demonstrates excellent performance in real-world software engineering including end-to-end project delivery, log analysis, code security, and ML tasks. On SWE-Pro it scores 56.22%, nearly matching Opus. It excels in professional office domains achieving the highest ELO among open-source models on GDPval-AA (1495), with significant improvement in complex editing for Office Suite. M2.7 maintains 97% skill adherence on 40 complex skills cases.
Capability Radar
Science uses a reasoning proxy when dedicated science benchmarks are unavailable.
Rankings
| Domain | #Rank | Score | Source |
|---|---|---|---|
| Agentic Capability | 89 | 49.0 | LS |
| Code Ranking | 64 | 73.0 | AA |
| General Ranking | 48 | 75.0 | AA |
| Science | 40 | 74.0 | AA |
Benchmark Scores (LLM Stats)
Agents
Code
General
AA Evaluation Indices
LLM Stats Category Scores
Pricing
Speed
Provider Price Ranking
Provider Price Ranking
29 providers
Compare pricing across different API providers for this model.