WildBench
WildBench evaluates AI models on challenging real-world user queries collected from the wild. It focuses on complex, multi-constraint instructions that test practical model capabilities beyond academic benchmarks.
Metrics
Win rate (%) on real-world user queries
Created By
Allen Institute for AI
Paper
View paper →Website
Visit website →Top Model Scores
| Rank | Model | Score | Date |
|---|---|---|---|
| 1 | Claude Opus 4.6 | 68.7% | 2026-02 |
| 2 | GPT-5.2 | 67.2% | 2026-03 |
| 3 | Gemini 3 Ultra | 63.8% | 2026-01 |
| 4 | Grok 4 | 61.4% | 2026-02 |
| 5 | Llama 4 405B | 57.1% | 2026-01 |
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Top: GPT-5.2 — 92.4%
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AlpacaEval 2.0
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Top: Claude Opus 4.6 — 72.1%
IFEval
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Top: Claude Opus 4.6 — 91.2%