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OpenAI

OpenAI for Science

We’re building the next great scientific instrument to accelerate discovery.

We're empowering scientists and mathematicians across disciplines, combining frontier AI models with research tools that extend human curiosity and drive discovery. Our goal is to help researchers explore more ideas, test hypotheses faster, and unlock discoveries that would otherwise take years, accelerating scientific progress in ways that meaningfully benefit humanity.

Why accelerating scientific progress matters

Science shapes everything, from the medicines that keep us healthy to the energy that powers our cities, the technologies that drive our economies, and the knowledge that defines our place in the universe. It’s the foundation of human progress. If we can compress decades of discovery into years, the ripple effects touch every part of society. Scientific results are visible, testable, and matter to everyone. OpenAI for Science advances our mission—ensuring that artificial general intelligence benefits all of humanity—by helping accelerate scientific progress.

A hand gently holds a butterfly in a lush, sunlit garden. The background is filled with greenery and orange flowers, evoking a calm, nature-focused atmosphere.

Built with scientists, for scientists

In partnership with scientists and mathematicians, we’re building AI systems that fit naturally into real research, designed to empower researchers to explore more ideas, test hypotheses faster, and uncover patterns that would have taken months or years to find alone. By deeply understanding how science actually happens, we’re working on tools that integrate seamlessly into existing workflows, from literature review and proof generation to modeling, simulation, and automation.

A person wearing blue gloves and a white lab coat labels a plastic test tube with a red marker in a laboratory setting. Several other test tubes are visible in a rack in the foreground, indicating an active scientific or medical testing environment.

How scientists and AI are already collaborating

Using our products, scientists across fields have gained a fast, knowledgeable research partner.

OpenAI for Science > Prism

Prism

Prism is a free, LaTeX-native workspace for scientific writing and collaboration, with GPT-5.2 integrated directly into the workflow. It brings drafting, revision, citations, equations, and publication prep into a single environment where AI works on the full context of a research project, supporting the iterative, careful process of scientific writing.

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GPT-5

With GPT‑5, mathematicians have generated correct proofs in minutes, physicists have seen the model rediscover hidden symmetry structures, biologists have validated mechanisms and follow-up experiments it proposed, and researchers across fields have used it to surface deep conceptual links in the literature that humans had missed.

OpenAI for Science > oss

Open Models

gpt-OSS provides open, inspectable models that researchers can run, modify, and build on directly. It enables experimentation, customization, and transparency for scientists who want to adapt AI to their own methods, data, and environments.

Prompting strategy for scientists

Working with GPT‑5 for science is a skill. The model is capable of deep reasoning, conceptual search, and formal computation, but scientists get the best results when they use it deliberately. The guidance below captures early lessons from researchers across math, physics, biology, and computer science on how to structure prompts, provide context, and collaborate with the model to accelerate real scientific work.

A ChatGPT message where a user asks for help tackling a black hole physics problem with parameters M and J. The interface shows the user message against a soft green-blue gradient background.
A ChatGPT conversation where the assistant displays a SymPy Python script used to verify PDE solutions. The code block shows imported SymPy functions and symbolic variable definitions.
A ChatGPT prompt displaying an uploaded PDF titled “Paper Draft v3.pdf.” The user asks ChatGPT to evaluate Section 3 of the paper for loopholes and suggest improvements.
A ChatGPT interface where a user pushes back on an earlier explanation about light-surface equations in plasma physics. The assistant replies with a corrected, more detailed derivation. Soft teal gradient background.

Starting with a simpler version of your question can dramatically improve performance on harder versions. This mirrors how humans work: a warm-up helps orient the model to the right structure.

Get involved with OpenAI for Science