Tongyi DeepResearch – open-source 30B MoE Model that rivals OpenAI DeepResearch

Posted by meander_water 11/2/2025

Tongyi DeepResearch – open-source 30B MoE Model that rivals OpenAI DeepResearch(tongyi-agent.github.io)

365 points | 153 commentspage 3

PunchTornado 11/3/2025|

it rivals a model that is obsolete? who is using openai deepresearch when there are so many better models out there?

DataDaemon 11/2/2025||

Unfortunately soon China will take lead in AI.

davidsainez 11/2/2025||

I have been very impressed with the Qwen3 series. I'm still evaluating them, and I generally take LLM benchmarks with a huge grain of salt, but their MoE models in particular seem to offer a lot of bang for the compute. But what makes you so sure they will take the lead?

greggh 11/3/2025||

Deepseek, Qwen, GLM (quite good). All being open and available for local use definitely puts them ahead in that space, which means a lot of the tinkerers and younger people learning to do things like train and fine-tune are getting good with Chinese models and I do think getting in early like that is a great way to gain mindshare in a space. Look at Apple or Microsoft doing everything they could early on to get their machines and software into schools as early as possible.

ninetyninenine 11/2/2025|||

Isn't this an indication they are already in the lead? They currently have the best model that beats everyone on all quantitative metrics? Are you implying that the US has a better model somewhere?

mike_hearn 11/3/2025||

They aren't in the lead. They are very close behind, but that's not hard given the quantity of freely published papers. They keep proving they can train models competitive with US models, but, only months after the fact. And at least some of the Chinese models were trained via distillation from US models. Probably not at Alibaba but it seems at least some models were.

aeve890 11/2/2025||

Unfortunately? May I ask why? What country would you like to be the lead in AI?

ninetyninenine 11/2/2025||

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victorbjorklund 11/2/2025|||

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Krasnol 11/2/2025|||

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GordonS 11/2/2025||

I rather think the GP was being sarcastic. At least, I hope they were.

Krasnol 11/3/2025||

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tomhow 11/4/2025|||

Please don't engage in political/nationalistic battle on HN, and make an effort to observe all guidelines when participating here.

https://news.ycombinator.com/newsguidelines.html

ninetyninenine 11/4/2025|||

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tomhow 11/4/2025||

Please don't troll on HN.

steveny3456 11/2/2025||

Juju

ninetyninenine 11/2/2025||

Is China dominating the US in terms of AI? Given that they currently have a model that beats the best models at all formal quantitative benchmarks?

What is the state of AI in China? My personal feeling is that it doesn't dominate the zeitgeist in China as it does in the US and despite this because of the massive amount of intellectual capital they have just a small portion of their software engineering talent working on this is enough to go head to head with us even though it only takes a fraction of their attention.

idiotsecant 11/2/2025||

I think the lesson of the Chinese catchup in AI is that there is a massive disadvantage in being first, in this domain. You can do all the hard work and your competitors can distill that work out of your model for pennies on the dollar. Why should anyone want to do the work?

MaxPock 11/2/2025||

This sounds like copium . If it was just about distillation,we'd be seeing many awesome models from Europe ,Japan and even India.

mike_hearn 11/3/2025||

It's certainly both a lot more than distillation and at least some Chinese labs have been cloning OpenAI via distillation. That's why they instituted much tighter ID verification requirements earlier this year.

No, the reason you don't see many open source models coming from the rest-of-world (other than Mistral in France) is that you still need a ton of capital to do it. China can compete because the CCP used a combination of the Great Firewall and lax copyright/patent enforcement to implement protectionism for internet services, which is a unique policy (one that obviously came with massive costs too). This allowed China to develop home grown tech companies which then have the datacenters, capital and talent density to train models. Rest of world didn't do this and wasn't able to build up domestic tech industries competitive with the USA.

MaxPock 11/3/2025||

There’s no Chinese lab that has been accused by OpenAI or anyone else of distillation. The accusations come from fringe right-wing media that are used to the “China only copies” trope. Training a model, by the way, is not about money, because many Western tech giants have more money than the CCP can allocate to Chinese labs. Apple, Meta, Amazon, SAP, IBM, and others have access to the same data as OpenAI and should thus be able to come up with a SOTA model in under a year, right? On lax copyright enforcement, I’d like to point out that it’s actually Western labs that have been taken to court for stealing content.

On matters protectionism,the Great Firewall was the best thing that China did.It prevented them from digital colonization like the rest of the world.

idiotsecant 11/3/2025|||

Oh, wow. 1) you're getting awfully defensive here. I didn't say there was some moral failing because Chinese shops distilled models from western ones. It's the smart play. I'm only commenting on how little of a moat first movers have. 2) if you can't admit that deepseek distilled their models from existing work I'm not sure what to tell you. The early models even identified themselves as chatGPT. It's widely known and has substantial evidence. This isn't team sports, you don't need to play defense. We deal with reality here.

mike_hearn 11/3/2025|||

They didn't make a big fuss about it but OpenAI have explained that they instituted ID and country verification because there were competitors distilling their models. Of their competitors do you really think Anthropic, Google or Meta were doing that? It's pretty clear who they were talking about.

Chinese labs are mostly (all?) privately funded, as far as I know. Alibaba isn't a SOE. That's why I didn't mention state subsidies, although that might be happening (and certainly is happening w.r.t. access to electricity).

I didn't mention lax copyright/patent enforcement in the context of AI, but rather, the prior years in which China was able to build up local tech firms capable of taking on the US tech firms. It's mostly in the past now, they don't need to do that stuff anymore.

seanmcdirmid 11/3/2025||

America continues to dominate in amount of money spent on AI resources but China has more value in the human and hardware resources it brings to bare.

China is also more willing to deploy AI apps that Americans would hesitate on, although I'm not sure I've seen much of it so far outside of Shenzhen cyberpunk clips. Let's see how this plays out in a decade.

yalogin 11/2/2025|

In my experience using these supposed expert models, they are all more or less the same given they all are trained on the same internet data. The differentiation and value is in the context window management and how relevant info from your session is pulled in. So it’s the interface to the model that makes all the difference. Even there the differences are quite minimal. That is because all these companies want to toe the line between providing functionality to keep the users engaged and pushing them to sign up for the subscription.

All this to ask the question, if I host these open source models locally, how is the user interface layer that remembers and picks the right data from my previous session and the agentic automation and others implemented? Do I have to do it myself or are the free options for that?

viksit 11/2/2025|

this is a great question. what are the main use cases that you have for this? i’ve been working on a library for something similar and exposing it via an mcp interface. would love to pick your brain on this (@viksit on twitter)