OpenAI offers free AI access to 100,000 academic researchers with GPT-5.6 Sol Pro through 2027

OpenAI will provide free AI models to select researchers - Engadget

The program, ChatGPT for Academic Researchers, will start with 10,000 participants this summer. OpenAI is launching a new program called ChatGPT for Academic Researchers that will offer free access to the company's AI models to 100,000 scientists, mathematicians and engineers. Researchers from "select academic institutions" included in the program will receive hands-on support from OpenAI, access to the company's latest GPT-5.6 Sol Pro model and be able to invite four collaborators from their institution to participate. The program will start with 10,000 participants this summer and scale up to 100,000 through 2027. OpenAI says offering free access to its AI tools "is part of a commitment of more than $250 million through 2027 to support external scientific research and discovery." As the company notes, researchers are already using AI models to sift through data and write grants -- this just makes the relationship a bit more formal. OpenAI's version of ChatGPT for schools, ChatGPT Edu, follows a similar logic. While the least charitable read of the program is that OpenAI is looking for new sources of training data, the company says that by default, researchers' data will not be used to train models. What handing out freebies to research institutions could generate, though, is more research breakthroughs that in some way involved a GPT model. And making more scientific fields dependent on the company's tools could also pave the way for future revenue from for-profit research. This isn't the first time the company has courted researchers. OpenAI introduced Prism in January, an AI-powered tool for working with scientific journals and documents. Prism is available to anyone with a ChatGPT account and can be used to verify things like research citations and formatting. OpenAI's early demo of the tool also included a way to generate lesson plans, one of the more tedious but critical tasks of research professors.

OpenAI gives 100,000 scientists free AI, and shows how

OpenAI is giving 100,000 academic researchers free access to its frontier models through 2027. The same week, it detailed how it slashed the cost of running its agents, including a model that used Codex to optimise OpenAI's own code. The giveaway and the cost-cutting are the same strategy: cheaper inference is what lets OpenAI give the models away. OpenAI made two announcements this week that look unrelated. One is generous. The other explains how it can afford to be. The generous one: OpenAI is giving 100,000 academic researchers free access to its frontier models through 2027, Axios reported. The programme, ChatGPT for Academic Researchers, starts with 10,000 users this summer and scales from there. Free frontier access for scientists Researchers get GPT-5.6 Sol Pro, OpenAI's top model, and can each invite up to four collaborators, the company said. Their data is not used to train models by default. Early institutions include the Institute for Advanced Study and the École normale supérieure. OpenAI frames it as accelerating science, and it forms part of a commitment of more than $250m through 2027 to fund outside research. Greg Brockman called it "more shots on goal against humanity's hardest problems." Not everyone reads it so warmly. Sceptics note the flywheel: hook researchers on a capped compute budget, learn from what they do, and keep the frontier compute in-house. Getting a generation of scientists to think inside ChatGPT is its own kind of moat. The engine underneath The second announcement is drier, and it is the reason the first is possible. OpenAI detailed how it slashed the cost of running its agents, The Deep View reported. The key piece is the agent harness. It sits under Codex and ChatGPT Work and directs the model, the tools and the context like a conductor. It is open-source, unlike Anthropic's Claude Code. It is also a token furnace. Early this year, some developers ran up $20,000 monthly bills as agents burned through compute. So OpenAI optimised it. GPT-5.6 Sol now beats Claude Fable 5 on a leading coding benchmark while using 54% fewer output tokens, the company says. A lighter model, GPT-5.5 Luna, costs 80% less than Sol. The model that cut its own bill The neatest detail is recursive. Using Codex, GPT-5.6 rewrote and optimised OpenAI's own production kernels, the low-level code that runs the models, The New Stack reported. OpenAI says that lifted token efficiency by more than 15%. The model helped cut its own cost. The timing is not an accident. Enterprises have soured on "tokenmaxxing," the habit of throwing raw compute at every task. Databricks says curbing AI cost is the top question it now hears from customers. Two sides of one strategy Put together, the two moves are a single play. Cheaper inference lets OpenAI give models away at the top of the funnel, to 100,000 scientists and to the other 990 million ChatGPT users it wants on agents. Generosity and cost control are the same strategy. There is a risk in it. Free frontier tools deepen the field's dependence on one company's stack, at the exact moment OpenAI is learning to run that stack for less. The cheaper it gets to serve, the more the world it serves belongs to OpenAI. Anthropic, as one poster put it, gets the next move.

OpenAI rolls out ChatGPT for Academic Researchers program for scientists, mathematicians and engineers

OpenAI has announced ChatGPT for Academic Researchers, a new program that will provide 100,000 researchers at selected academic institutions with free access to its frontier AI models and tools through 2027. The initiative is designed for scientists, mathematicians, and engineers, supporting research activities across disciplines, from hypothesis generation and coding to grant writing, publishing, and scientific analysis. ChatGPT for Academic Researchers: Features Participants will receive free access to ChatGPT, ChatGPT Work, and Codex, including GPT-5.6 Sol Pro at launch and the broader GPT-5.6 family of models. Key highlights include: * GPT-5.6 Sol Pro at launch * Expanded Deep Research capabilities * Higher usage limits * Larger context windows * Business-grade privacy and security protections * Data not used to train OpenAI's models by default Researchers can also access more than 75 life science skills covering genetics, genomics, sequencing, single-cell analysis, protein modeling, and drug discovery. Connectors provide access to scientific literature, public genomic and clinical databases, satellite imagery, computational notebooks, data platforms, and reference managers. Together, these capabilities support scientific reasoning, agentic execution, and research workflows across disciplines. AI adoption in scientific research According to OpenAI, around 1.3 million people use ChatGPT for advanced science and mathematics every week, generating approximately 8.4 million messages. The company also noted that acknowledgements of ChatGPT in arXiv mathematics papers have increased over the past six months, reflecting wider adoption of AI in mathematical research. OpenAI said researchers are using ChatGPT and Codex across nearly every stage of scientific work. Some supported use cases include: * Interrogating ideas and acquiring knowledge * Hypothesis generation * Literature reviews * Coding, debugging, and data analysis * Grant proposal preparation * Manuscript drafting and publishing * Building reproducible research workflows * Creating materials to communicate research findings ChatGPT primarily supports idea exploration, literature reviews, hypothesis generation, and communicating research findings, while Codex focuses on research execution and formal analysis. ChatGPT Work is designed for longer projects such as finding funding opportunities, preparing grant applications, reviewing literature, drafting manuscripts, and creating materials to communicate research results. OpenAI highlighted several research examples. Physicist Rogerio Jorge and his team are using AI to develop open-source fusion research software used by industry and national laboratories to design fusion energy devices. In theoretical computer science, Barna Saha, Yinzhan Xu, and Christopher Ye used GPT-5.5 Pro to develop a proof establishing new limits on how efficiently computers can solve high-dimensional geometry problems before validating and refining the results themselves. Researchers in the top 20% of AI usage within their field are also nearly twice as likely as their peers to assign AI tasks estimated to take four hours or longer, accounting for nearly 7% of their requests compared with 3.5% among other researchers in the same field. GPT-5.6 models and benchmark performance The GPT-5.6 family includes: * GPT-5.6 Terra for everyday research tasks * GPT-5.6 Luna for faster responses on lighter workloads * GPT-5.6 Sol for advanced scientific and mathematical reasoning According to OpenAI: * GPT-5.6 Sol scored 83% on FrontierMath Tier 4, which measures research-level mathematical reasoning, compared with 72.5% for GPT-5.5. * GPT-5.6 Sol Pro solved 31.5% of tasks on GeneBench Pro, which evaluates complex biological data analysis and scientific reasoning. Training and support The program includes training tailored to different levels of AI experience, ranging from first-time users to researchers developing advanced AI applications. Participants will also receive hands-on support from specialists familiar with research workflows, including assistance with integrating the tools into their research. OpenAI also plans to provide opportunities for researchers to share practical use cases and feedback. Availability The initial rollout begins this summer with 10,000 researchers, with access already available at the Institute for Advanced Study (IAS) and École normale supérieure (ENS). OpenAI plans to expand the program to 100,000 researchers by 2027. To apply: * Researchers must belong to a qualifying, degree-granting academic institution with a high level of research activity. * Applicants must verify their institutional affiliation. * Applicants must provide details about their active research and intended scientific use. * Approved participants can invite up to four collaborators from the same institution, with each collaborator required to verify their affiliation and counting toward the program's total number of accounts. For institutions using ChatGPT Edu, access provided through the program will be coordinated through the institution's existing workspace. Applications are open now.

OpenAI offers free AI access to 100,000 academic researchers By Investing.com

Investing.com -- OpenAI announced Wednesday it will provide 100,000 researchers at academic institutions with free access to its frontier AI models through a new program called ChatGPT for Academic Researchers. The program will begin with 10,000 researchers this summer and expand to 100,000 researchers through 2027. Access is already available at institutions including the Institute for Advanced Study and École normale supérieure. Participants will receive access to OpenAI's frontier models, including GPT-5.6 Sol Pro at launch. Each researcher can invite up to four collaborators from their institution. The workspaces include business-grade privacy and security protections, and data is not used to train models by default. The initiative is part of a commitment of more than $250 million through 2027 to support external scientific research and discovery. This includes NextGenAI, a $50 million initiative supporting research institutions, and work with the Department of Energy's Genesis Mission to bring frontier AI to researchers at national laboratories and universities. OpenAI reported that approximately 1.3 million people use ChatGPT for advanced science and mathematics each week, generating about 8.4 million messages. In mathematics, papers acknowledging ChatGPT's contribution on arXiv increased from 14 in February to 100 in the first three weeks of July. Researchers in the top 20% of AI usage within their field submit requests for tasks estimated to require four hours or more at nearly twice the rate of their peers, at 7% compared with 3.5%. Participants will receive access to the GPT-5.6 family of models. GPT-5.6 Sol scores 83% on FrontierMath Tier 4, which measures research-level mathematical reasoning, compared with 72.5% for GPT-5.5. On GeneBench Pro, which evaluates complex biological data analysis and scientific reasoning, GPT-5.6 Sol Pro solves 31.5% of tasks. The program will offer training tailored to different experience levels and access to specialists familiar with research workflows. The initial program is open to qualifying researchers at selected academic institutions that are recognized, degree-granting colleges or universities with a high level of research activity. This article was generated with the support of AI and reviewed by an editor. For more information see our T&C.