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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.

Community Sentiment Analysis

Real-time analysis of public opinion and engagement

Sentiment Distribution

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

Critical Perspectives

Community concerns and opposing viewpoints

1

Praise for rapid shipping

Several replies cheer the Qwen team for shipping weeklyโ€”short, enthusiastic reactions (e.g., "๐Ÿ”ฅ") 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 โ€œisnโ€™t a good lookโ€ and expresses doubt theyโ€™ll surpass OpenAI, urging creators not to cling to another company for attention.

Q

@QuantumBJJ_

China once again cooks USA

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@MrZ2128

US so cooked

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A

@Astrodevil_

So qwen team is shipping every week ๐Ÿ”ฅ

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Supporting Voices

Community members who agree with this perspective

1

Open-source triumph โ€” 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 โ€” 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 โ€” 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 โ€” 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 โ€” 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 โ€” Many propose community-driven challenges, benchmarks, and collaborative testing on the GitHub repo and Hugging Face to push capabilities and vet reliability

Community validation โ€” 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 โ€” Commenters emphasize how a performant open-source web agent lowers barriers and could accelerate innovation across builders and labs

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

7

Next-step curiosity โ€” 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 โ€” 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.

A

@Ali_TongyiLab

7/7๐Ÿš€ 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! ๐Ÿ”— Homepage:

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@Ali_TongyiLab

5/7๐Ÿ“ˆ 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)

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@Ali_TongyiLab

6/7 ๐ŸŒ Application. Tongyi DeepResearch agent is already powering real-world applications. ๐Ÿ”น Gaode Mate: An AI copilot in the Amap navigation app for planning complex multi-day trips. ๐Ÿ”น Tongyi FaRui: A legal research agent that analyzes case law and statutes, providing

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