tau-bench: τ-bench
Multi-turn tool-use benchmark for agent behavior in realistic retail and airline customer-service tasks, measuring whether models complete tasks through APIs while following policy constraints.
Models ranked
29
tracked on this benchmark
Score band
95.3 – 61.1
best → lowest tracked
Snapshot trend
-7.71
May 5 → Jun 7 · 13 models
Leaderboard
Tracked models ranked by % Task Success (higher is better).
Notes: Confidence: high. DAT-3780 weekly best-of refresh: benchlm.ai TAU-bench snapshot lists Claude Mythos Preview at 89.2%.
Notes: DAT-5460 source reconciliation: benchlm.ai tau-bench snapshot lists Claude Opus 4.6 at 84.8.
Notes: DAT-5460 source reconciliation: benchlm.ai tau-bench snapshot lists Grok 4.20 at 78.9.
How to read this benchmark
This benchmark scores models where higher is better. Use scores for directional filtering and shortlisting, not universal quality ranking; then validate pricing, context window, provider availability, and fit for your workload.
Trust this score when
- There is a fresh timestamped snapshot (or multiple snapshots) for this benchmark.
- The model list covers the same version family you can actually deploy today.
- Top candidates overlap with your required routing and feature requirements.
Be cautious when
- There is only one benchmark snapshot or the dataset appears stale.
- The benchmark metric direction is opposite of your decision objective.
- The score difference between options is narrow and likely within implementation variance.
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Last reviewed: Apr 26, 2026