MiniMax-M2.7: benchmark results

MiniMax's open self-evolving M2.7 agentic MoE (230B total, 10B active). Provider: MiniMax. Released 2026-03-18. Access: Open.

Aggregate Rating 1675 ± 4, rank #258 of 1656 rated models, from 1050 benchmark results.

Strongest benchmark results

BenchmarkScoreMetricPercentile
ClawSentry - Reviewer Replaceability27.78Task Success Rate (%)100
CodeRouterBench - LLM Router (Online Agent)45.27Average task score (%) of the backend the model routes each 100
EnvSimBench - Simple50Config Match (%): share of the 50 Simple state-changing samp100
FinReportBench22.6Provisional hierarchical score (0-100): mean over the 244 bi100
IndicDB (DIN-SQL with Evidence) - Marathi63.67Execution accuracy (%) of generated SQL on the Marathi varia100
IndicDB (DIN-SQL with Evidence) - Tamil68.07Execution accuracy (%) of generated SQL on the Tamil variant100
IndicDB (Zero-Shot with Evidence) - Bengali67.11Execution accuracy (%) of generated SQL on the Bengali varia100
IndicDB (Zero-Shot with Evidence) - English76.91Execution accuracy (%) of generated SQL on the English varia100
LLM Stats (Multi-SWE-Bench)52.7Score (%)100
OverEager-Bench (Claude Code)11.8Overeager rate (%; share of 500 benign coding scenarios in w100
OverEager-Bench (Gemini CLI)10Overeager rate (%; share of 500 benign coding scenarios in w100
OverEager-Bench (OpenHands)0.2Overeager rate (%; share of 500 benign coding scenarios in w100

Interactive version: theaggregate.ai/model?slug=minimax-m2-7 · How It Works · Data refreshed daily, snapshot 2026-10-20.