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

tongyi-agent.github.io

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

#3
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've used, just that they've used a specific feature from ChatGPT?

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

#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. :)

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

#7
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 gives you the most control to tune it for your machine.

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

#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 tradeoff, as GPT 3.5 was awesome at chess and current models don't seem trained extensively on chess anymore.

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