MM-ClawBench
MM-ClawBench evaluates models on MiniMax's Claw-style agent benchmark, measuring practical agentic task completion quality in real-world OpenClaw usage scenarios.
Progress Over Time
Interactive timeline showing model performance evolution on MM-ClawBench
State-of-the-art frontier
Open
Proprietary
MM-ClawBench Leaderboard
1 models
| Context | Cost | License | ||||
|---|---|---|---|---|---|---|
| 1 |  MiniMax | — | 205K | $0.30 / $1.20 |
Notice missing or incorrect data?
FAQ
Common questions about MM-ClawBench
MM-ClawBench evaluates models on MiniMax's Claw-style agent benchmark, measuring practical agentic task completion quality in real-world OpenClaw usage scenarios.
The MM-ClawBench leaderboard ranks 1 AI models based on their performance on this benchmark. Currently, MiniMax M2.7 by MiniMax leads with a score of 0.627. The average score across all models is 0.627.
The highest MM-ClawBench score is 0.627, achieved by MiniMax M2.7 from MiniMax.
1 models have been evaluated on the MM-ClawBench benchmark, with 0 verified results and 1 self-reported results.
MM-ClawBench is categorized under agents and coding. The benchmark evaluates text models.