I'm hiring. Come help us build SLURM 2.0 and (try to) make GPUs behave: job-boards.greenhouse.io/thealleninstit… Ai2 is a one of a kind place and my team is doing great work. Join us!

Ai2 released OLMoE today. It's our best model to date. - 1.3B active, 6.9B total parameters, 64 experts per layer - Trained on 5T tokens from DCLM baseline + Dolma - New preview of Tulu 3 post training recipe - Fully open source - Actually SOTA for ~1B active params I'm most

This is really neat. I had fun being a part of getting this out the door. Go Ai2 -- yet again pushing forward open science!

We're hiring! Come help us redefine how researchers and engineers use state-of-the-art GPU clusters: job-boards.greenhouse.io/thealleninstit…

Come join my team! We work on really interesting systems that brilliant practitioners use to build and run frontier AI workloads.

Yet another big step forward for fully open models. It’s been really exciting to work on the underlying compute infrastructure. …and if that sounds fun / interesting (which it is) — join my team: job-boards.greenhouse.io/thealleninstit…

kicking off 2025 with our OLMo 2 tech report while payin homage to the sequelest of sequels 🫡 🚗 2 OLMo 2 Furious 🔥 is everythin we learned since OLMo 1, with deep dives into: 🚖 stable pretrain 🚔 lr anneal 🤝 data curricula 🤝 soups 🚘 tulu post-train 🚜 compute infra 👇🧵

Can AI really help with literature reviews? 🧐 Meet Ai2 ScholarQA, an experimental solution that allows you to ask questions that require multiple scientific papers to answer. It gives more in-depth, detailed, and contextual answers with table comparisons, expandable sections

Here is Tülu 3 405B 🐫 our open-source post-training model that surpasses the performance of DeepSeek-V3! The last member of the Tülu 3 family demonstrates that our recipe, which includes Reinforcement Learning from Verifiable Rewards (RVLR) scales to 405B - with performance on

This is really cool. A SoTA model on your phone. Now I can chat with our models while I'm riding the ferry (though the group of regulars I sit w/ is also pretty fun). Yet another important release from Ai2 that both demonstrates what's possible and makes AI more accessible.

So many tokens in PDFs 📜 yet so hard to extract them 🔎 Not anymore! olmOCR gives you plain text version of any doc you can think of: science papers, old scans, brochures with weird layouts, even handwriting ✍️ Try it today 👇

We’re excited to share some updates to Ai2 ScholarQA: 🗂️ You can now sign in via Google to save your query history across devices and browsers. 📚 We added 108M+ paper abstracts to our corpus - expect to get even better responses! ✨ The backbone model has been updated to the

Announcing OLMo 2 32B: the first fully open model to beat GPT 3.5 & GPT-4o mini on a suite of popular, multi-skill benchmarks. Comparable to best open-weight models, but a fraction of training compute. When you have a good recipe, ✨ magical things happen when you scale it up!

My team had fun getting these up quickly. It definitely took a bit of elbow grease/GPU sorcery b/c the hardware is so new. Onward 🚀!

For years it’s been an open question — how much is a language model learning and synthesizing information, and how much is it just memorizing and reciting? Introducing OLMoTrace, a new feature in the Ai2 Playground that begins to shed some light. 🔦

We're excited to round out the OLMo 2 family with its smallest member, OLMo 2 1B, surpassing peer models like Gemma 3 1B or Llama 3.2 1B. The 1B model should enable rapid iteration for researchers, more local development, and a more complete picture of how our recipe scales.

Have questions? We’re an open book! We’re excited to host an AMA to answer your Qs about OLMo, our family of open language models. 🗓️ When: May 8, 8-10 am PT 🌐 Where: r/huggingface 🧠 Why: Gain insights from our expert researchers Chat soon!

We’re live on Reddit! Ask us Anything about our OLMo family of models. We have six of our researchers on hand to answer all your questions.

My latest post: The American DeepSeek Project Build fully open models in the US in the next two years to enable a flourishing, global scientific AI ecosystem to balance China's surge in open-source and an alternative to building products ontop of leading closed models.

With fresh support of $75M from U.S. National Science Foundation and $77M from @NVIDIA, we’re set to scale our open model ecosystem, bolster the infrastructure behind it, and fast‑track reproducible AI research to unlock the next wave of scientific discovery. 💡