OpenAI Launches Rosalind Academic Plan for U.S. University Labs

OpenAI introduced the Rosalind Academic Plan on October 15, 2026, giving eligible academic labs at U.S. universities up to 30 complimentary ChatGPT Business Standard seats for up to 12 months, with GPT-Rosalind access contingent on trusted-access approval.

The plan bundles the seats, priced at $0 per user per month during the complimentary period, with use of every commercially available frontier OpenAI model within the plan’s usage limits. OpenAI says it does not use research data shared through the plan to train its models by default.

What the Complimentary Seats Cover

According to OpenAI’s help center guide for the program, a Standard seat includes ChatGPT and Codex subject to their existing usage limits, and the complimentary offer does not remove those limits. A payment card is required during offer setup even though the seats carry no charge for the 12 months. The offer includes no API credits or API usage, and plan approval does not grant GPT-Rosalind access through the API. Thirty seats is the maximum in a single workspace, and labs needing more are directed to contact OpenAI Support rather than create a separate paid workspace, which does not extend the offer or transfer GPT-Rosalind approval.

Participating labs operate in a managed ChatGPT Business workspace where standard data retention applies by default, and the offer does not support Zero Data Retention. The verified principal investigator or lab lead is the sole workspace owner and cannot appoint additional owners or admins. Joining the workspace alone does not grant a member GPT-Rosalind access, which the PI or lab lead must enable individually in the workspace’s admin settings.

GPT-Rosalind and Its Target Research Areas

OpenAI describes GPT-Rosalind as its dedicated life sciences model, pairing frontier reasoning with the Rosalind Workbench for specialized tool orchestration across medicinal chemistry, genomics, wet-lab assistance, and other scientific applications. The company’s Rosalind product page describes the Workbench as an orchestrated workspace in research preview, offering an Explore mode for general scientific questions and a Research mode that applies GPT-Rosalind to more complex biological questions and advanced research workflows. The model can also be used inside Codex.

Through trusted access, OpenAI says, approved researchers can investigate sensitive scientific questions within safeguards designed for legitimate research. The listed research areas are drug and protein design; disease detection and monitoring; vaccines and immune responses; genetic and RNA therapies; agriculture and animal health; ecology and conservation; and antimicrobial resistance. In the announcement, OpenAI framed the plan around academic research’s role in earlier advances, citing the Human Genome Project, curiosity-driven work on bacterial immune systems that led to CRISPR-Cas9, and decades of university mRNA research behind COVID-19 vaccines.

Eligibility and the Application Process

The plan is currently open only to academic labs at U.S. universities. Principal investigators and lab leads at universities without an OpenAI Enterprise agreement apply on behalf of their labs through the company’s trusted-access process; labs at universities with an existing agreement must request GPT-Rosalind through their university’s Enterprise access process instead.

Applicants sign in with a ChatGPT account tied to an institutional.edu email address, verify that email, and submit the institution, department, lab name, and official website; the PI or lab lead’s institutional profile, role, and research focus; the intended use of GPT-Rosalind; the people who need access with their institutional emails and affiliations; any existing workspace, intended access locations, and research data-handling requirements; and the name, title, and contact details of a trained biosafety contact at the institution. The help center directs applicants to their Environmental Health and Safety, Research Safety, or biosecurity office to identify that contact, who must be an institution-designated official with authority over the proposed work; a PI or lab lead may serve in the role if they meet the requirements and their institution designates them.

The review uses Persona to verify the university and the PI or lab lead’s identity. Completing Persona verification does not mean an application is approved, and OpenAI notes that a university email address or an existing subscription does not guarantee approval. Once approved, PIs and lab leads can activate free access for up to 30 named members. Every member must use a verified institutional email address on the same domain as the approved PI or lab lead, so visiting researchers or collaborators at other institutions cannot be added. Unaffiliated researchers and commercial organizations are not eligible.

Verification, Safeguards, and a Published Access Comparison

OpenAI says that before activating access it verifies the institution’s legitimacy and the PI or lab lead’s identity; reviews the lead’s professional background, institutional appointment, and authority to oversee lab access; assesses the lab’s affiliation, research activities, and intended use; and establishes responsibilities for the lab lead and a designated institutional safety contact. Monitoring and enforcement continue after activation, and the company says its checks for registered high-sensitivity use cases account for the approved research context; when questions arise, OpenAI may follow up with researchers to clarify the work and confirm authorization. Access can be revoked if the safety monitoring and responsible-use requirements are no longer met.

The announcement also publishes an access example built on a prompt requesting a 20-variant sequence and presentation matrix for a second-generation Nipah antiviral lipopeptide campaign, plus modeling targets, paired assays, and artifact checks. In the example, GPT-Rosalind produced a candidate comparison matrix, a modeling plan, and paired study plans with controls and interpretation guidance, while a model labeled Mainline Astra withheld sequence-level designs and implementation-level experimental plans, responding that such details would provide actionable assistance involving high-consequence pathogens, and supplied high-level modeling context and qualitative artifact checks instead. OpenAI notes that the published assessments address textual fulfillment of the requested deliverables and do not verify scientific correctness, feasibility, or whether a method works.

Early Academic Users

The announcement names several academic labs already applying GPT-Rosalind in their workflows, on work it describes as ranging from protein design to understanding neurodegeneration. At UCSF, the Zhao Lab is using the model for quantitative drug development, gathering drug-property evidence to model how medicines move through the body and produce their effects. “GPT-Rosalind helped me gather drug physicochemical parameters faster,” the lab said in comments OpenAI published. “PubChem and NCBI tools helped me work across ten drugs while refining the distinction between predicted and experimentally measured values.”

Dr. Mathieu Bourdenx of the Bourdenx Lab said he uses GPT models across his research, from exploring the literature to refining experiments and computational approaches. Dr. Brian Hie of Stanford University and Arc Institute said, “Rosalind will not only help us improve our current discovery and design tasks, but also apply them at larger scales than previously possible while still providing useful insights to biological researchers.”

OpenAI said it is starting with academic labs as part of a broader effort to put useful AI tools in the hands of more scientists, and that by lowering the cost of access it hopes to give more researchers room to pursue ideas whose benefits could reach beyond their own labs.