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Pith Number

pith:W6AUY5MM

pith:2025:W6AUY5MMPVV5I44UCQMODSCQO4
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Tongyi DeepResearch Technical Report

Bo Zhang, Chenxi Wang, Dingchu Zhang, Donglei Yu, Fei Huang, Gang Fu, Guangyu Li, Guoxin Chen, Hailong Yin, Haiyang Shen, Huifeng Yin, Jialong Wu, Jiayin Yang, Jingren Zhou, Junkai Zhang, Jun Lin, Kuan Li, Kui Zeng, Liangcai Su, Litu Ou, Liwen Zhang, Li Yang, Maojia Song, Ming Yan, Minpeng Liao, Pengjun Xie, Peng Xia, Qian Xiao, Rui Min, Ruixue Ding, Rui Ye, Runnan Fang, Shaowei Chen, Shen Huang, Shihang Wang, Shihao Cai, Tongyi DeepResearch Team: Baixuan Li, Weizhou Shen, Wenbiao Yin, Xiaobin Wang, Xin Guan, Xinmiao Yu, Xinyu Geng, Xinyu Wang, Xixi Wu, Xuanzhong Chen, Yida Zhao, Yingcheng Shi, Yong Jiang, Yuning Wu, Zhengwei Tao, Zhen Zhang, Zhongwang Zhang, Zhuo Chen, Zijian Li, Zile Qiao

Tongyi DeepResearch, a sparsely activated 30.5-billion-parameter agentic model, achieves state-of-the-art performance on long-horizon deep research benchmarks.

arxiv:2510.24701 v2 · 2025-10-28 · cs.CL · cs.AI · cs.IR · cs.LG · cs.MA

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Record completeness

1 Bitcoin timestamp
2 Internet Archive
3 Author claim open · sign in to claim
4 Citations open
5 Replications open
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Claims

C1strongest claim

Tongyi DeepResearch, featuring 30.5 billion total parameters, with only 3.3 billion activated per token, achieves state-of-the-art performance across a range of agentic deep research benchmarks, including Humanity's Last Exam, BrowseComp, BrowseComp-ZH, WebWalkerQA, xbench-DeepSearch, FRAMES and xbench-DeepSearch-2510.

C2weakest assumption

That the fully automatic data synthesis pipeline produces training data of sufficient quality and diversity to enable genuine long-horizon research agency without human annotation or verification.

C3one line summary

Tongyi DeepResearch is a new agentic LLM that reaches state-of-the-art results on deep research benchmarks including Humanity's Last Exam and BrowseComp through fully automatic data synthesis and specialized training environments.

Formal links

3 machine-checked theorem links

Cited by

32 papers in Pith

Receipt and verification
First computed 2026-05-17T23:38:52.956713Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

b7814c758c7d6bd473941418e1c850771ed65b4dc0fb596c301f813c7b3ea475

Aliases

arxiv: 2510.24701 · arxiv_version: 2510.24701v2 · doi: 10.48550/arxiv.2510.24701 · pith_short_12: W6AUY5MMPVV5 · pith_short_16: W6AUY5MMPVV5I44U · pith_short_8: W6AUY5MM
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Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/W6AUY5MMPVV5I44UCQMODSCQO4 \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: b7814c758c7d6bd473941418e1c850771ed65b4dc0fb596c301f813c7b3ea475
Canonical record JSON
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    "submitted_at": "2025-10-28T17:53:02Z",
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