Understand this story
On October 23, 2026, Hugging Face's Thomas Wolf announced a collaboration with TIGEM, the University of Naples Federico II, and Zhongguancun Academy to train and release the open-source DNA model Carbon-X. The model can directly read raw DNA and interpret it in natural language, with open weights, and its training data excluded human and animal viruses. According to its release information, Carbon-X scored 67% on its own DNA benchmark, higher than Claude Opus 5.5's 61% and Gemini 4 Argon's 50%, and within less than one point of GPT-6.1 Sol while costing about 1,000 times less. On October 26, MarkTechPost reported that Carbon-X is a 14.8B-parameter decoder-only DNA language model based on Qwen3-14B, using a hybrid tokenizer with 5,515 newly added DNA tokens, supporting a 40,960-token context, with weights released under Apache 2.0 and runnable in bfloat16 on a single 80GB GPU. The report also stated that Hugging Face self-reported an average of 66.7% across 5 DNA benchmarks, with BioReason Coding reaching
AI-generated from public reports
Latest development · Report
Hugging Face Releases 14.8B Open-Source DNA Language Model Carbon-XDevelopments
1 confirmed developments
- Source:Thomas Wolf
Reports and discussion timeline
Browse reports and discussion by time. Their evidence levels remain distinct.
Oct 26
MarkTechPost
Hugging Face Releases 14.8B Open-Source DNA Language Model Carbon-X
Hugging Face Bio has released Carbon-X, a 14.8B-parameter decoder-only DNA language model that can directly read raw DNA and answer in English, with weights released under Apache 2.0. The model is based on Qwen3-14B and uses a hybrid tokenizer that adds 5,515 DNA tokens, supports a 40,960-token context, and can run in bfloat16 on a single 80GB GPU; the official GGUF Q8_0 is 15.8GB. Hugging Face self-reports an average of 66.7% across 5 DNA benchmarks, with BioReason Coding reaching 74.9%, but only 29.8% on GenomeQA splice-site questions, and it has not undergone clinical validation.
Oct 23
t3n
Hugging Face open-sources Carbon-X: analyzing DNA through dialogue based on Qwen3-14B
Hugging Face, together with Zhongguancun Academy, the Telethon Institute of Genetics and Medicine, and the University of Naples Federico II, released the open-source model Carbon-X, which builds a hybrid tokenizer on Qwen3-14B and can directly analyze DNA sequences through English dialogue. The model has 14.8B parameters and achieves an average accuracy of 66.7% across five genetic variant interpretation tests, 27 percentage points higher than the base Qwen3-14B and close to GPT-6.1 Sol's 67.5%. The cost per query is about 1800 times lower than GPT-6.1 Sol; screening all 2.4 million variants of uncertain significance in ClinVar costs about $300, and the model can run locally on a single GPU or even a laptop.
Latent Space
Latent Space summary: Black October security incident wave
Latent Space compiles the vulnerabilities and intrusion incidents that emerged in a concentrated burst over roughly 48 hours from October 21 to 22 into Black October, covering the PHP2Shell unauthenticated RCE, a CVSS 10 vulnerability present in GitLab versions since 2014 (fixed in 19.5.1), LiteLLM 1.107.0 carrying a password stealer, and the eMudhra CA having weak keys and exiting the CA business. The article also mentions that Microsoft attributed the ConnectWise supply chain attack to Storm-0940, which used the open-source agent penetration testing framework ARTEX to launch roughly 2,900 login attempts per minute against more than 2,250 Microsoft 365 tenants. The author also includes the opposing view, which holds that this looks more like a defensive audit and that there is currently no evidence of large-scale exploitation.
cnBeta
Hugging Face Launches Carbon-X, an Open-Source DNA Model Based on Qwen3-14B
Hugging Face, together with research labs in Italy and China, launched the open-source model Carbon-X, which is trained on genomic sequences and natural language based on Qwen3-14B and can answer questions about DNA sequences, predict the effects of mutations, and generate new sequences. Hugging Face says that on five DNA understanding and generation benchmarks, Carbon-X's average score is close to GPT-6.1 Sol, while its inference cost is only 1/1800 of the latter, and it scores 27 points higher than Qwen3-14B. The model can run locally, and its training data explicitly excludes virus-related data.
cnBetaRelated discussion
cnBeta joined this discussion
This post contributes to heat; it is not a formal report or confirmed fact.
Phoenix Tech
Hugging Face launches Carbon-X, a 14-billion-parameter DNA model built on Qwen3-14B
Hugging Face announced on Thursday the launch of Carbon-X, an open-source model with 14 billion parameters for DNA understanding and generation, obtained by training Qwen3-14B on genomic sequences and natural language. It integrates DNA sequences and natural language into a single model, allowing researchers to ask questions about specific DNA sequences, predict the effects of mutations, and generate new DNA sequences; it can also serve as a sub-agent to help other models interpret DNA sequences. Hugging Face says that on five DNA understanding and generation benchmarks, Carbon-X outperforms all other open-source models it evaluated, with an average score close to GPT-6.1 Sol, but at an inference cost per question of only 1/1800 of the latter, and 27 points higher than Qwen3-14B.
CNET
Hugging Face releases the Carbon-X model, enabling conversation with DNA sequences in natural language
Hugging Face has released Carbon-X, the newest and most capable model in the Carbon series; researchers can input DNA sequences and ask questions in natural language to obtain interpretations, predictions, or explanations. Researcher Lewis Tunstall said the model is best at predicting the effects of mutations and completing DNA sequences, for example determining whether a given sequence change might be harmful, and can run sensitive or unpublished sequences on local hardware. Hugging Face also noted limitations such as counting errors, fabricating sequence identity or function when prompt information is insufficient, and degraded output quality on long sequences, and it publicly released the training recipe for community scrutiny.
Thomas WolfSelected
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.
Oct 22
Clément Delangue
Hugging Face open-sources DNA model Carbon-X, mid-trained on Qwen3-14B
Hugging Face co-founder Clément Delangue announced the open-source DNA model Carbon-X, obtained by mid-training Qwen3-14B on 300B tokens of DNA, English, and interleaved data, using a hybrid tokenizer with BPE for English and a 6-mer tokenizer for DNA. The model surpasses all open-source language models it evaluated on five DNA understanding and generation benchmarks, improving on Qwen3-14B by 27 points, with API costs 1,800 times lower than GPT 6.1 Sol. The model is released on Hugging Face under the Apache 2.0 license.
Business Insider Tech
Hugging Face Releases Open-Source Model Carbon-X, Which Can Analyze and Generate DNA Sequences Using Natural Language
Hugging Face has released the open-source model Carbon-X, combining DNA analysis and generation with natural language so that researchers can ask questions directly and receive predictions and explanations. The model is based on Qwen3-14B and was trained on genomic sequences and natural language from humans, other mammals, plants, and fungi, with viruses explicitly excluded from the training data. Researchers can run it locally, avoiding the sharing of sensitive patient data with external AI companies, and can also generate new DNA sequences to assist gene therapy research.
Wired AI
Hugging Face Releases Open-Source DNA Model Carbon-X, Runs Locally on a Laptop
Hugging Face on Thursday released the open-source DNA understanding model Carbon-X, which can run locally on a laptop, letting users ask in natural language how DNA changes affect gene activity and health. The model was developed in collaboration with researchers at Zhongguancun Academy and the University of Naples Federico II; it extends the vocabulary of an existing language model to read DNA in six-letter units and was further trained on 300 billion tokens of DNA sequences, English text, and samples pairing DNA with biological descriptions. The model has 14B parameters and can process sequences of about 50,000 base pairs at a time; it cannot upload a complete human genome. The developers also note that the prediction accuracy has not yet been validated through wet-lab experiments.
Heat trend for this story
- Current
- 5
- Period peak
- 34 Oct 23 19:00
- 24-hour change
- -72%
Move the pointer or select the chart to inspect hourly heat. Use the left and right arrow keys with a keyboard.