Higher-compute GPT-5.5 variant optimized for the hardest professional workloads, producing more precise answers at significantly higher latency and cost.
Model updates refreshed1d agoJun 8, 2026news + changelog
Introducing GPT-5.5 | OpenAI Skip to main content Research Products Business Developers Company Foundation (opens in a new window) Log in Try ChatGPT (opens in a new window) Research Products Business Developers Company Foundation (opens in a new window) Try ChatGPT (opens in a new window) Login OpenAI Model capabilities Model capabilities Next-generation inference efficiency Advancing cybersecurity for everyone’s safety Availability and pricing Evaluations April 23, 2026 Pro
We’ve been researching new ways for ChatGPT memory to carry context across conversations and keep it useful over time. Today, that work is rolling out as a more capable memory system in ChatGPT. https
We’ve been researching new ways for ChatGPT memory to carry context across conversations and keep it useful over time. Today, that work is rolling out as a more capable memory system in ChatGPT. https://t.co/0MyFKCe2Mu
What happened when one of our models found a counterexample to an 80-year-old Erdős conjecture? Researchers @alexwei_, @HongxunWu, and @wjmzbmr1 shared the story on the OpenAI Podcast with @AndrewMayn
What happened when one of our models found a counterexample to an 80-year-old Erdős conjecture? Researchers @alexwei_, @HongxunWu, and @wjmzbmr1 shared the story on the OpenAI Podcast with @AndrewMayne and explained how mathematicians and models can work together to make new https://t.co/bQQ6Bvr8Qh
We’ve been researching new ways for ChatGPT memory to carry context across conversations and keep it useful over time. Today, that work is rolling out as a more capable memory system in ChatGPT. https
We’ve been researching new ways for ChatGPT memory to carry context across conversations and keep it useful over time. Today, that work is rolling out as a more capable memory system in ChatGPT. https://t.co/0MyFKCe2Mu
OpenAI frontier models and Codex are now generally available on AWS, giving enterprises a new way to build on Amazon Bedrock with OpenAI through the security, compliance, and governance workflows they
OpenAI frontier models and Codex are now generally available on AWS, giving enterprises a new way to build on Amazon Bedrock with OpenAI through the security, compliance, and governance workflows they already use. This is also the beginning of a broader expansion of OpenAI
Humanoid-GPT: Scaling Data and Structure for Zero-Shot Motion Tracking
We introduce Humanoid-GPT, a GPT-style Transformer with causal attention trained on a billion-scale motion corpus for whole-body control. Unlike prior shallow MLP trackers constrained by scarce data and an agility-generalization trade-off, Humanoid-GPT is pre-trained on a 2B-frame retargeted corpus that unifies all major mocap datasets with large-scale in-house recordings. Scaling both data and model capacity yields a single generative Transformer that tracks highly dynamic behaviors while achieving unprecedented zero-shot generalization to unseen motions and control tasks. Extensive experiments and scaling analyses show that our model establishes a new performance frontier, demonstrating robust zero-shot generalization to unseen tasks while simultaneously tracking highly dynamic and complex motions.
OpenWebRL: Demystifying Online Multi-turn Reinforcement Learning for Visual Web Agents
Building capable visual web agents requires long-horizon reasoning, precise grounding, and robust interaction with dynamic real-world websites. Despite rapid progress, the strongest systems remain largely proprietary, while open agents still depend heavily on supervised post-training over large collections of curated web trajectories. This dependence creates a major scalability bottleneck: high-quality demonstrations are expensive to collect, and static datasets offer limited coverage of the diverse, ever-changing open web. Although online RL has shown promise for text-based agents, its potential for training visual web agents directly on live websites remains largely underexplored. In this paper, we introduce OpenWebRL, an open framework for training visual web agents with online multi-turn RL on real websites. OpenWebRL covers the full training pipeline, including scalable live-browser infrastructure, supervised initialization, multimodal context management, trajectory-level success judging, and efficient multi-turn policy optimization. Using this framework, we train OpenWebRL-4B, which establishes a new open-source state of the art on challenging live-web benchmarks. With only 0.4K initialization trajectories and 2.2K open-ended RL training tasks, OpenWebRL-4B achieves 67.0% success on Online-Mind2Web and 64.0% on DeepShop, outperforming prior open agents of similar or larger scale and remaining competitive with proprietary systems including OpenAI CUA and Gemini CUA. Beyond strong benchmark performance, we systematically study the key design choices that make online RL effective for visual web agents, and analyze how RL improves agentic reasoning. Overall, our work offers a practical path toward building more capable, reproducible, and cost-efficient open web agents. We will release our training data, models, and code to support future research.
Introducing GPT‑5 for developers | OpenAI Skip to main content Research Products Business Developers Company Foundation (opens in a new window) Log in Try ChatGPT (opens in a new window) Research Products Business Developers Company Foundation (opens in a new window) Try ChatGPT (opens in a new window) Login OpenAI Introduction Introduction New features Safety Availability & pricing Detailed benchmarks August 7, 2025 Product Introducing GPT‑5 for developers The best model
GPT-5.5 Pro Model | OpenAI API Home API Docs Guides and concepts for the OpenAI API API reference Endpoints, parameters, and responses Codex Docs Guides, concepts, and product docs for Codex Use cases Example workflows and tasks teams hand to Codex ChatGPT Apps SDK Build apps to extend ChatGPT Commerce Build commerce flows in ChatGPT Ads Publish and measure ads in ChatGPT Resources Showcase Demo apps to get inspired Blog Learnings and experiences from developers Cookbook Note
GPT-5.5 Pro Model | OpenAI API Home API Docs Guides and concepts for the OpenAI API API reference Endpoints, parameters, and responses Codex Docs Guides, concepts, and product docs for Codex Use cases Example workflows and tasks teams hand to Codex ChatGPT Apps SDK Build apps to extend ChatGPT Commerce Build commerce flows in ChatGPT Ads Publish and measure ads in ChatGPT Resources Showcase Demo apps to get inspired Blog Learnings and experiences from developers Cookbook Note
