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.

Model: http://huggingface.co/HuggingFaceBio/Carbon-X

Blog: http://huggingface.co/spaces/HuggingFaceBio/Carbon-X-Release