This is over a month old, they released the weights a long time ago.
That's OK — not all of us follow all the progress on a daily basis, and a model that is a month old doesn't become useless just by being a month old!
Tongyi DeepResearch – open-source 30B MoE Model that rivals OpenAI DeepResearch
41–50 of 156 posts
Re: Tongyi DeepResearch – open-source 30B MoE Model that rivals OpenAI DeepResearch
#42I recently got a 5090 with 64 GB of RAM (intel cpu). Was just looking for a strong model I can host locally. If I had performance of GPT4-o, I'd be content. Are there any suggestions or cases where people got disappointed?
5090 has 32GB of RAM. Not sure if that’s enough to fit this model.
Re: Tongyi DeepResearch – open-source 30B MoE Model that rivals OpenAI DeepResearch
#43I recently got a 5090 with 64 GB of RAM (intel cpu). Was just looking for a strong model I can host locally. If I had performance of GPT4-o, I'd be content. Are there any suggestions or cases where people got disappointed?
5090 has 32GB of RAM. Not sure if that’s enough to fit this model.
It should fit enough of the layers to make it reasonably performant.
Re: Tongyi DeepResearch – open-source 30B MoE Model that rivals OpenAI DeepResearch
#44I recently got a 5090 with 64 GB of RAM (intel cpu). Was just looking for a strong model I can host locally. If I had performance of GPT4-o, I'd be content. Are there any suggestions or cases where people got disappointed?
GPT-OSS-20B at 4- or 8-bits is probably your best bet? Qwen3-30b-a3b probably the next best option. Maybe there exists some 1.7 or 2 bit version of GPT-OSS-120B
Re: Tongyi DeepResearch – open-source 30B MoE Model that rivals OpenAI DeepResearch
#45In 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 to…
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)
Re: Tongyi DeepResearch – open-source 30B MoE Model that rivals OpenAI DeepResearch
#46I recently got a 5090 with 64 GB of RAM (intel cpu). Was just looking for a strong model I can host locally. If I had performance of GPT4-o, I'd be content. Are there any suggestions or cases where people got disappointed?
5090 has 32GB of RAM. Not sure if that’s enough to fit this model.
LlamaCPP supports offloading some experts in a MoE model to CPU. The results are very good and even weaker GPUs can run larger models at reasonable speeds.
n-cpu-moe in https://github.com/ggml-org/llama.cpp/blob/master/tools/serv...
Re: Tongyi DeepResearch – open-source 30B MoE Model that rivals OpenAI DeepResearch
#47It 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…
Isn't the whole point of the MOE architecture exactly this?
That you can individually train and improve smaller segments as necessary
Re: Tongyi DeepResearch – open-source 30B MoE Model that rivals OpenAI DeepResearch
#48Sunday 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.
This is the way. I managed to run (super) tiny models on CPU only with this approach.
Re: Tongyi DeepResearch – open-source 30B MoE Model that rivals OpenAI DeepResearch
#49Unfortunately soon China will take lead in AI.
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?
Re: Tongyi DeepResearch – open-source 30B MoE Model that rivals OpenAI DeepResearch
#50Is 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.