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xbench-DeepSearch benchmark
AI model leaderboard for the xbench-DeepSearch benchmark. Compare how large language models score on xbench-DeepSearch, see the full ranking, and understand what this AI benchmark measures. Tongyi DeepResearch currently leads with 75. Agentic deep-search benchmark from xbench — evaluates multi-source web research and synthesis.
Leaderboard
| # | Model | Organization | Score | Variant | Source |
|---|---|---|---|---|---|
| #1 | Tongyi DeepResearch | Alibaba-NLP | 75 | react-avg@3 | official ↗ |
| #2 | DeepSeek-V3.1 | DeepSeek | 71 | react-cited-tongyi | official ↗ |
| #3 | GLM 4.5 | Zhipu AI | 70 | react-cited-tongyi | official ↗ |
| #4 | o3 | OpenAI | 67 | react-cited-tongyi | official ↗ |
| #5 | Claude Sonnet 4 | Anthropic | 65 | react-cited-tongyi | official ↗ |
| #6 | Kimi K2 | Moonshot | 50 | react-cited-tongyi | official ↗ |
Frequently asked questions about xbench-DeepSearch
What is the xbench-DeepSearch benchmark?
Agentic deep-search benchmark from xbench — evaluates multi-source web research and synthesis.
How is the xbench-DeepSearch benchmark scored?
xbench-DeepSearch is scored using the accuracy metric, where a higher score is better. GenAIList aggregates reported scores from model providers and papers into a single ranked leaderboard.
Which AI model scores highest on xbench-DeepSearch?
As of the latest reported scores on GenAIList, Tongyi DeepResearch achieves the highest result on xbench-DeepSearch with a score of 75.
Is a higher xbench-DeepSearch score better?
Yes. On xbench-DeepSearch a higher score indicates better performance, so models near the top of the leaderboard are the strongest.