OpenAI launches GPT-Rosalind, a reasoning model built for life sciences research

OpenAI says the model sets itself apart from earlier GPT versions by being tuned specifically for scientific workflows. It's meant to reason more accurately about molecules, proteins, genes, signaling pathways, and disease biology, while making better use of scientific tools and databases across multi-step workflows. Supported tasks include literature research, interpreting sequence-function relationships, experiment planning, and data analysis.

In OpenAI's own evaluations, GPT-Rosalind outperforms its predecessors GPT-5, GPT-5.2, and GPT-5.4 across chemistry, biochemistry and protein understanding, phylogenetics, experiment design, and tool usage.

On the public BixBench benchmark for bioinformatics and data analysis, GPT-Rosalind scored 0.751 on Pass@1. According to OpenAI, that puts it ahead of GPT-5.4 (0.732), Grok 4.2 (0.698), GPT-5 (0.728), and Gemini 3.1 Pro (0.550). On LABBench2, which covers tasks like literature research, database access, sequence manipulation, and protocol design, GPT-Rosalind beats GPT-5.4 on 6 out of 11 tasks, OpenAI says. The biggest jump came in CloningQA, which requires fully designing DNA and enzyme reagents for molecular cloning protocols.

A free plugin that connects more than 50 scientific data sources

Alongside the model, OpenAI is releasing a freely available life sciences research plugin for Codex on GitHub. The plugin provides modular skills for common research workflows and hooks models up to more than 50 public multi-omics databases, literature sources, and biology tools. It spans human genetics, functional genomics, protein structure, biochemistry, clinical evidence, and public study discovery.

OpenAI says the plugin works as an orchestration layer to help researchers handle broad, ambiguous, and multi-step questions. Enterprise users can pair it with GPT-Rosalind, while everyone else can use it with the standard OpenAI models.

A planned model series and a Los Alamos partnership

GPT-Rosalind is launching as a research preview in ChatGPT, Codex, and the API, but only for qualified enterprise customers in the US through a "Trusted Access" program. During the preview, usage won't eat into existing credits or tokens. OpenAI will share pricing and broader availability later.

To gain access, organizations must meet three requirements: they have to be doing legitimate scientific research with clear public benefit, they need proper governance, compliance, and abuse-prevention controls, and access has to be limited to approved users in secure, managed environments.

OpenAI says GPT-Rosalind is just the first in a planned series of models aimed at the life sciences. The company plans to keep expanding biochemical reasoning capabilities for tool-heavy, long-horizon research workflows.

Current customers and partners already working with GPT-Rosalind include Amgen, Novo Nordisk, Moderna, Thermo Fisher Scientific, Oracle Health and Life Sciences, NVIDIA, the Allen Institute, Benchling, and the UCSF School of Pharmacy.