LiveBrowseComp - Avg@4 - Entertainment: leaderboard
Evaluates deep web research on the LiveBrowseComp paper snapshot using recent long-tail facts and a common search, page retrieval and Python scaffold. Scores are accuracy averaged over four attempts (avg@4), not pass@4. The shared budget is 250 steps and 256k context; source model labels are retained. Domain results are slices of the same paper evaluation. This series reports LiveBrowseComp - Avg@4 - Entertainment using Avg@4 Accuracy (%).
Metric: Avg@4 Accuracy (%). Source: arxiv.org. Saturation forecast: Around July 2027. 11 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | GLM-5 | 52.1 | #149 |
| 2 | Claude Sonnet 4.6 | 43 | #94 |
| 3 | GPT-5.4 | 43 | #83 |
| 4 | DeepSeek V4 Pro | 41.1 | #112 |
| 5 | Gemini 3.1 Pro (Preview) | 39.3 | #64 |
| 6 | DeepSeek V3.2 | 35 | #210 |
| 7 | GLM-5.1 | 33.5 | #109 |
| 8 | Kimi K2.6 | 27.8 | #113 |
| 9 | Kimi K2.5 | 21.8 | #152 |
| 10 | MiniMax-M2.5 | 20.5 | #316 |
No result here: #3 Claude Opus 5.5, #6 GPT-6 Astra, #7 GPT-6.1 Sol.
Interactive version: theaggregate.ai/benchmark?slug=livebrowsecomp-avg-4-entertainment · How It Works · Data refreshed daily, snapshot 2026-11-05.