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

tongyi-agent.github.io

11–20 of 156 posts

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

#12

Isn't OpenIA "Deep research" (not "DeepResearch") a methodology/tooling thing, and you'll get different responses depending on what specific model you use with it? As far as the UI allows you to, you could use Deep research with GPT-5, GPT-4o, o3 and so on, and that'll have an impact on the responses. Skimming the paper and searching for some simple terms makes it seem like they never expand on what exact models they…

[deleted]

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

#13

I hope the translation for this is actually "Agree" Deep research. Just a dig at "You are absolutely right!" sycophancy.

TIL the "full" name of Alibaba Qwen is 通義千問(romanized as "Tongyi Qianwen", something along "knows all thousand questions"), of which the first half without the Chinese accent flags is romanized identically to "同意", meaning "same intents" or "agreed".

The Chinese version of the link says "通义 DeepResearch" in the title, so doesn't look like the "agree" to be the case. Completely agreed that it would be hilarious.

1: https://www.alibabacloud.com/en/solutions/generative-ai/qwen...

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

#14
post #5

Sunday morning, and I find myself wondering how the engineering tinkerer is supposed to best self-host these models? I'd love to load this up on the old 2080ti with 128gb of vram and play, even slowly. I'm curious what the current recommendation on that path looks like. Constraints are the fun part here. I know this isn't the 8x Blackwell Lamborghini, that's the point. :)

If you just want to get something running locally as fast as possible to play with (the 2080ti typically had 11gb of VRAM which will be one of the main limiting factors), the ollama app will run most of these models locally with minimum user effort:

https://ollama.com/

If you really do have a 2080ti with 128gb of VRAM, we'd love to hear more about how you did it!

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

#15
post #5

Sunday morning, and I find myself wondering how the engineering tinkerer is supposed to best self-host these models? I'd love to load this up on the old 2080ti with 128gb of vram and play, even slowly. I'm curious what the current recommendation on that path looks like. Constraints are the fun part here. I know this isn't the 8x Blackwell Lamborghini, that's the point. :)

Im sure this guy has some helpful hints on that: https://youtube.com/@azisk

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

#16
post #5

Sunday morning, and I find myself wondering how the engineering tinkerer is supposed to best self-host these models? I'd love to load this up on the old 2080ti with 128gb of vram and play, even slowly. I'm curious what the current recommendation on that path looks like. Constraints are the fun part here. I know this isn't the 8x Blackwell Lamborghini, that's the point. :)

llama.cpp + quantized: https://huggingface.co/bartowski/Alibaba-NLP_Tongyi-DeepRese...

get the biggest one that will fit in your vram.

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

#17

Isn't OpenIA "Deep research" (not "DeepResearch") a methodology/tooling thing, and you'll get different responses depending on what specific model you use with it? As far as the UI allows you to, you could use Deep research with GPT-5, GPT-4o, o3 and so on, and that'll have an impact on the responses. Skimming the paper and searching for some simple terms makes it seem like they never expand on what exact models they…

At this point "deep research" is more of a pattern - OpenAI and Perplexity and Google Gemini all offer products with that name which work essentially the same way, and Anthropic and Grok have similar products with a slightly different name attached.

The pattern is effectively long-running research tasks that drive a search tool. You give them a prompt, they churn away for 5-10 minutes running searches and they output a report (with "citations") at the end.

This Tongyi model has been fine-tuned to be really good at using its search tool in a loop to produce a report.

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

#18
post #8

It makes me wonder if we'll see an explosion of purpose trained LLMs because we hit diminishing returns on invest with pre training or if it takes a couple of months to fold these advantages back into the frontier models. Given the size of frontier models I would assume that they can incorporate many specializations and the most lasting thing here is the training environment. But there is probably already some tradeo…

-> GPT 3.5 was awesome at chess I don't agree with this. I did try to play chess with GPT3.5 and it was horrible. Full of hallucinations.

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

#19
It still feels to me like OpenAI has zero moat. There are like 5 paid competitors + open source models.

I switch between gemini and ChatGpt whenever I feel one fails to fully grasp what I want, I do coding in claude.

How are they supposed to become the 1 trillion dollar company they want to be, with strong competition and open source disruptions every few months?

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

#20
post #11
post #9

This whole series of work is quite cool. The use of `word-break: break-word;` makes this really hard to read though.

I actually can’t read it for some reason? My brain just can’t connect the words

so it appears the entire text has been Translated with non-breaking space unicode x00a0 instead of normal spaces x0020, so the web layout is considering all paragraph text as a super-long single word ('the\00a0quick\00a0\brown\00a0fox' instead of 'the quick brown fox') - the non-breaking space character appears identically to breaking-space when rendered but underlying coding breaks the concept of "break at end of word" because there is no end as 00a0 literally means "non-breaking"). per Copilot spending a half hour explaining this to me, apparently this can be fixed by opening web browser developer view, and copy/pasting this code into the console.

function replaceInTextNodes(node) { if (node.nodeType === Node.TEXT_NODE) { node.nodeValue = node.nodeValue .replace(/\u00A0/g, ' '); } else { node.childNodes.forEach(replaceInTextNodes); } }

replaceInTextNodes(document.body);

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