tau-Rec: leaderboard
Metric: pass^1 (0-1 scaled to %), the mean strict success rate per trial: a recommendation succeeds only when every required typed constraint holds against the catalog and every active policy is respected; the agent recommends one movie from a 153-title TMDB catalog to a GPT-5 mini user simulator through dialogue and catalog tools on 60 tasks (constraints revealed up front, only on asking, or never), 4 trials per task, agent temperature 0 where supported; higher is better. Source: arxiv.org. Saturation forecast: Around December 2026. 9 models tracked.
Top models
| # | Model | Score |
|---|---|---|
| 1 | DeepSeek V4 Flash (Max) | 57.1 |
| 2 | DeepSeek V4 Flash (High) | 56 |
| 3 | GPT-5.4 (Medium) | 55.1 |
| 4 | DeepSeek V4 Flash (Non-reasoning) | 54.6 |
| 5 | Claude Sonnet 4.6 | 53.7 |
| 6 | GPT-5.4 (Non-reasoning) | 47.1 |
| 7 | GPT-5 Mini | 41.7 |
| 8 | Gemini 2.5 Flash | 27.5 |
| 9 | Qwen 3 32B | 27.1 |
Interactive version: theaggregate.ai/benchmark?slug=tau-rec · How It Works · Data refreshed daily, snapshot 2026-09-29.