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Tongyi DeepResearch: Open-Source Web Agent Matches OpenAI

Tongyi DeepResearch: fully open-source Web Agent matching OpenAI performance with 30B (Activated 3B) parameters. Scores: 32.9, 45.3, 75.0 on key benchmarks.

@Ali_TongyiLabposted on X

1/7 We're launching Tongyi DeepResearch, the first fully open-source Web Agent to achieve performance on par with OpenAI's Deep Research with only 30B (Activated 3B) parameters! Tongyi DeepResearch agent demonstrates state-of-the-art results, scoring 32.9 on Humanity's Last Exam, 45.3 on BrowseComp, and 75.0 on the xbench-DeepSearch benchmark.

View original tweet on X →

Community Sentiment Analysis

Real-time analysis of public opinion and engagement

Sentiment Distribution

72% Engaged
64% Positive
Positive
64%
Negative
8%
Neutral
28%

Key Takeaways

What the community is saying — both sides

Supporting

1

Open-source triumph — Many readers are ecstatic that a 30B model can match proprietary systems, praising the project as a game-changer for accessibility and customization and celebrating the release with excitement and thanks

Open-source triumph — Many readers are ecstatic that a 30B model can match proprietary systems, praising the project as a game-changer for accessibility and customization and celebrating the release with excitement and thanks.

2

Technical scrutiny — A notable thread of questions focuses on tool-use reliability and long-horizon planning

people want details on how the agent manages multi-step workflows, prevents context overload, and ensures dependable tool calls.

3

Scalability & cost — Several users ask how performance scales to larger datasets and deployments and request side-by-side comparisons of quality vs

cost against OpenAI, Claude, and Google.

4

Real-world adoption — Interest is high in practical integrations (e

g. , Gaode Mate, legal research), with readers asking where adoption will take off first and suggesting AR, navigation, and enterprise legal use-cases.

5

Community validation — Many propose community-driven challenges, benchmarks, and collaborative testing on the GitHub repo and Hugging Face to push capabilities and vet reliability

Community validation — Many propose community-driven challenges, benchmarks, and collaborative testing on the GitHub repo and Hugging Face to push capabilities and vet reliability.

6

Recognition of impact — Commenters emphasize how a performant open-source web agent lowers barriers and could accelerate innovation across builders and labs

Recognition of impact — Commenters emphasize how a performant open-source web agent lowers barriers and could accelerate innovation across builders and labs.

7

Next-step curiosity — Folks are eager to try the model, ask about roadmaps, pricing, and demos, and some offer to help run or host tests to stress real-world behavior

Next-step curiosity — Folks are eager to try the model, ask about roadmaps, pricing, and demos, and some offer to help run or host tests to stress real-world behavior.

Opposing

1

Praise for rapid shipping

Several replies cheer the Qwen team for shipping weekly—short, enthusiastic reactions (e.g., "🔥") emphasize momentum and appreciation for fast iteration.

2

Competitive, nationalistic bragging

Comments such as "China once again cooks USA" and "US so cooked" frame the discussion as a tech rivalry, celebrating perceived Chinese dominance.

3

Casual skepticism and banter

One-liners like "ngmi or wagmi?", "wen moon?", and "I got distracted after the first sentence" inject crypto-style shorthand, jokes, and mild indifference into the thread.

4

Critical pushback on comparisons to OpenAI

A reply cautions that constantly comparing Chinese models to OpenAI “isn’t a good look” and expresses doubt they’ll surpass OpenAI, urging creators not to cling to another company for attention.

Top Reactions

Most popular replies, ranked by engagement

A

@Ali_TongyiLab

Supporting

7/7🚀 Try it out! Tongyi DeepResearch agent marks a significant step towards AI that can autonomously turn information into insight. We're open-sourcing the model, framework, and complete solutions to empower the community. Dive in and build with us! 🔗 Homepage:

213
6
16.4K
A

@Ali_TongyiLab

Supporting

5/7📈 Performance (Heavy Mode). For maximum capability, our "Heavy Mode" uses the Research-Synthesis framework. Multiple agents research in parallel using our IterResearch paradigm, preventing context overload. A final agent synthesizes their findings, pushing our 30B (A3B)

166
1
81.0K
A

@Ali_TongyiLab

Supporting

6/7 🌐 Application. Tongyi DeepResearch agent is already powering real-world applications. 🔹 Gaode Mate: An AI copilot in the Amap navigation app for planning complex multi-day trips. 🔹 Tongyi FaRui: A legal research agent that analyzes case law and statutes, providing

122
1
16.5K
Q

@QuantumBJJ_

Opposing

China once again cooks USA

9
0
1.0K
M

@MrZ2128

Opposing

US so cooked

5
0
763
A

@Astrodevil_

Opposing

So qwen team is shipping every week 🔥

1
0
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