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OSU-NLP Group trained a ~frontier "Deep Research Agent" using 32 H100 GPUs and…

2026-06-17 · 22:54 UTC ·@ysu_nlp ·1 min read

Brief

OSU-NLP Group trained a ~frontier "Deep Research Agent" using 32 H100 GPUs and ~8,000 synthetic samples, applying SFT, mid-training, and RL to produce models spanning 2B–35B parameters. They claim a small team and a few hundred Ks can yield specialized, near-frontier models and have open-sourced paper (arXiv:2605.24218), code, weights, data, and a demo.

Source evidence

We trained a ~frontier Deep Research Agent on academic budget

> 32 H100s
> 8K synthetic samples
> fully open training infra + recipe (SFT, mid-training, RL)
> models of diff sizes (2B -> 35B) ready to use out of the box

This is yet another demonstration of how the frontier of AI is changing. We have reached a point where open models + a small capable team + a few hundred Ks can produce specialized models with ~frontier capabilities. The future of AI doesn’t have to be held in a chokehold by a handful of closed models.

We've open-sourced everything we've built and learned from this project. Hope it helps the community build more!

📌 Project: osu-nlp-group.github.io/QUES…
📌 Paper: arxiv.org/abs/2605.24218
📌 Code: github.com/OSU-NLP-Group/QUE…
📌 Model Weights and Data: huggingface.co/collections/o…
📌 Demo: huggingface.co/spaces/osunlp…

Amazing effort led by @jianxie_ (our 1st year student!!), Tianhe Lin, Zilu Wang. joint with @hhsun1 and the @osunlp team. thanks @amazon Xiangjun Wang for a gift that covers the compute and fruitful discussion.