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Better prompt caching for GPT-6

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Higher cache hit rates and new tools to help persistent agents run faster and cost less. GPT‑6 enables persistent agents to work for hours on complex tasks, from refactoring codebases to producing well-researched documents and presentations. The applications behind these agents make a series of API requests that build on one another, often carrying forward the same instructions, tool definitions, and context from earlier turns. OpenAI caches that shared context to reuse computation across requests, reducing response times and giving developers discounts of up to 90% on cached input tokens.…

OpenAI · 22 Sep 2026 · 23:00 CESTRead story →Original ↗

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Introducing GPT-6 Sol and Luna

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More ways to bring frontier intelligence into the work you do every day. Earlier this month, we introduced GPT‑6 Astra, the most intelligent and aligned model in the world. While the most demanding and important projects still call for Astra’s full depth, work happens at different scales, rhythms, and budgets. That’s why we’re expanding the GPT‑6 universe with GPT‑6 Sol and GPT‑6 Luna. GPT‑6 Astra introduced a new generation of intelligence—these models help distribute the benefits of that intelligence by advancing the frontier on cost efficiency. We trained GPT‑6 Sol…

OpenAI · 22 Sep 2026 · 20:00 CESTRead story →Original ↗

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Transformers now runs llama.cpp quants

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Running AI models on your laptop has become much easier, and llama.cpp has been a big part of that. Its inference engine powers local AI tools such as Ollama, LM Studio, and Jan. Alongside projects like MLX, it has helped make local inference a practical option for everyday use. This is where we are right now. And i’m not gonna lie it feels pretty magical 🧙‍♀️Qwen3.6 27B running inside of Pi coding agent via Llama.cpp on the MacBook ProFor non-trivial tasks on the @huggingface codebases, this feels very, very close…

Hugging Face · 22 Sep 2026 · 02:00 CESTRead story →Original ↗

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Priorities and principles for effective third party assessments

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Frontier AI labs carry an immense responsibility in training, evaluating, and deploying models safely. Third party assessments are a critical part of balancing that responsibility, expanding opportunities for input on AI safety, keeping the world informed, and keeping labs accountable to clear and independently supported safety claims. As part of our efforts to pace the frontier, OpenAI is committed to supporting independent assessments with deep levels of access across training, evaluation, and deployment. That access should enable assessors to challenge our assumptions, identify risks we may have missed, and reach…

OpenAI · 22 Sep 2026 · 02:00 CESTRead story →Original ↗

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Advisory Group on Mathematics and Artificial Intelligence

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On August 28, we began training a new internal model. In addition to resolving the Navier–Stokes Millennium Prize problem⁠, this model has now resolved more than 100 long-standing open problems across most areas of mathematics. The pace of its progress⁠ in mathematics has surprised the mathematicians within OpenAI. This has led to internal discussions on the best way to inform the community of the rapid progress to prepare and adapt the field. Mathematics is a fundamental science, and novel discoveries may result in a wide range of applications. That makes…

OpenAI · 21 Sep 2026 · 14:00 CESTRead story →Original ↗

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Building standards for the next phase of AI

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Our mission is to ensure that artificial general intelligence benefits all of humanity. As outlined recently by Sam Altman and Jakub Pachocki, we prioritize our work towards this mission with three main goals: Navigate the next period of AI progress, by building an automated AI researcher, iterating with it on the alignment problem, and finding ways for people to remain part of the self-improvement loop. Deliver the benefits of scientific progress and economic growth that very intelligent machines enable. AI is accelerating our own research and engineering, and AI-enabled research…

OpenAI · 21 Sep 2026 · 12:00 CESTRead story →Original ↗

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Expanding OpenAI Academy with new learning paths

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Role-based learning helps employees, developers, leaders, educators, and students build practical AI skills and demonstrate what they’ve learned. Using AI safely and effectively takes practice. People need to learn how to apply it to the work in front of them, whether they’re improving a daily workflow, building a product, leading a team, or teaching a class. At OpenAI, we treat learning as part of deployment. Today, we’re expanding OpenAI Academy with new courses for developers, leaders, educators, and college students. These join Apply AI at Work, which helps people build…

OpenAI · 21 Sep 2026 · 09:00 CESTRead story →Original ↗

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tokenizers v1: encode, decode and scaling, measured

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As models become faster and workloads scale, that balance begins to shift. Training on massive datasets, serving many concurrent requests, or repeatedly processing long inputs can put enough pressure on the tokenizer that it starves the model of data. This is why we have chosen to heavily focus on performance for the upcoming version 1 of tokenizers. Tokenization should be light and should scale with your workflow. Your GPUs should never sit idle waiting for the CPU to complete its tokenization. In this article, we look at what makes v1…

Hugging Face · 21 Sep 2026 · 02:00 CESTRead story →Original ↗

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V7 cuts costs 78% while boosting accuracy with GPT-5.6 Luna

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Using GPT-5.6, V7 turns scattered company files into context agents can use to complete complex, source-linked work.

OpenAI · 21 Sep 2026 · 02:00 CESTRead story →Original ↗

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A new chapter for MIT Reads

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As it marks its 10-year anniversary, MIT Reads is being reimagined for the age of artificial intelligence. Recognizing the need to foster social connection and a sense of our shared humanity, the popular MIT Libraries’ program will turn its focus to fiction and memoir, and to the particular power of stories to help us understand ourselves and our place in the world. “At MIT, we spend a great deal of time on imagining and building for the future. Reading fiction prompts us to think about how what we build might…

MIT News · 18 Sep 2026 · 18:30 CESTRead story →Original ↗

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How Cooley is accelerating IPO work with ChatGPT

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Cooley’s GO Public offering uses ChatGPT Work to surface issues earlier, focus expertise, and help clients reach market faster. Cooley is an international law firm with a reputation for helping companies navigate capital markets and initial public offerings (IPOs). In 2025, the firm advised on 180 deals globally, totaling more than $51.5 billion in deal volume. Cooley has a decade-long track record at the top of the US issuer-side IPO market and has advised on more venture-backed IPOs than any other firm over the past 20-plus years. Capital markets involve…

OpenAI · 17 Sep 2026 · 14:00 CESTRead story →Original ↗

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Introducing Astra for Law

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Our most powerful model, configured into a new AI foundation for law. Today, we’re introducing Astra for Law: a new foundation for law firms and legal technology companies to build AI products and workflows around their expertise. It combines GPT‑6 Astra, our latest and most powerful model, with settings, tools, and context tailored for professional legal work. API customers including Harvey and Legora will be able to build on Astra for Law, bringing this intelligence into their own products and workflows. As our frontier models advance, we’ll bring these legal…

OpenAI · 17 Sep 2026 · 02:00 CESTRead story →Original ↗