Hugging Face, together with TIGEM and other institutions, releases the open-source DNA model Carbon-X
Thomas Wolf announced that, in collaboration with TIGEM, the University of Naples Federico II, and Zhongguancun Academy, they trained Carbon-X, an open 14B model that can directly read raw DNA and interpret it in natural language. It scores 67% on its DNA benchmark, above Claude Opus 5.5's 61% and Gemini 4 Argon's 50%, and is less than one point behind GPT-6.1 Sol while costing about 1,000 times less. The training data excludes human and animal viruses, the weights are open, and the model can run on hardware accessible to academia, such as a laptop.
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SelectedAI score 69
The authors have disclosed Carbon-X's benchmark comparisons, training data trade-offs, and the open-source conditions under which it can run on a laptop, making it easier to assess the feasibility of an open approach to biological models.
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Body
While I was writing this, my AI assistant got cut off by a bio safety filter. It was summarizing my own team's notes on the model we released today 😅
Frontier labs are moving fast into biology but the scientists and clinicians who'd get the most out of these models are unfortunately the ones running into walls like this one (and every day).
So we partnered with TIGEM (Telethon Institute of Genetics and Medicine), Naple "Federico II" University and Zhongguancun Academy to train Carbon-X.
Carbon-X is an open 14B model that reads raw DNA and talks about it in plain English. On our DNA benchmarks it scores 67%, vs 61% for Claude Opus 5.5 and 50% for Gemini 4 Argon, and its within a point of GPT-6.1 Sol at about 1000x lower cost.
We kept human and animal viruses out of the training data. The weights are open and the model runs on hardware accessible to academia (a laptop).
One example from the blog: give frontier models an 8kb stretch of the NF1 gene with a mutation at a splice site. Most of them call it benign, refuse, or run out of tokens. Carbon-X says pathogenic, because the mutation breaks the splice site.
This century, biology may be where AI matters most. We want to get there with the safety work done in the open and every lab in the world able to build on it. Go try it, and tell us what you find.