MUTATE: leaderboard
Divergent thinking is a core dimension of creativity, yet existing evaluations of Large Language Models (LLMs) treat them as single-turn text generations, failing to capture how an agent reasons through iterative interaction. To address this, we introduce MUTATE, an interactive benchmark designed to evaluate agentic divergent thinking at two levels: path-level, where an agent discovers multiple al
Metric: Overall (self-reported). Source: benchmarklist.com. Saturation forecast: Around May 2027. 4 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | Claude Sonnet 4.6 | 73.2 | #90 |
| 2 | GPT-5.4 | 67.9 | #79 |
| 3 | Qwen 3 235B A22B | 64.3 | #313 |
| 4 | Llama 4 Maverick | 51.8 | #464 |
No result here: #3 Claude Opus 5.5, #6 GPT-6 Astra, #7 GPT-6.1 Sol.
Interactive version: theaggregate.ai/benchmark?slug=mutate · How It Works · Data refreshed daily, snapshot 2026-10-20.