Official news, first rumor reports and substantive progress. Each entry keeps the information published at that time.
OpenAI released Images 2.6 across ChatGPT, Codex, and the API on November 4, adding GIF generation and image-input editing. The API offers Flare and Sunburst tiers, and OpenAI says generation is roughly 50% faster than the previous version; ChatGPT and Codex availability covers all subscription tiers worldwide.
OpenAI's API pricing docs now include a "Legal model configurations" section listing gpt-6-astra-law — a law-focused variant of its GPT-6 Astra flagship — at $10 per million input tokens, $50 per million output tokens, and $1 per million cached input tokens. OpenAI says the promotional pricing holds at least through December 31, 2026, marking the first specialized Astra configuration to surface.
OpenAI's API changelog says GPT-6.1 Terra is released, a fast, efficient model for visual reasoning, precise computer use, and clear, natural writing. See the GPT-6 guide for prompting and migration guidance.
OpenAI Developers said GPT-6.1 Terra is also coming to the API and Codex, for building apps and agents that interpret images, navigate software and take action, with fast computer use at a lower cost for high-volume workflows.
OpenAI introduced GPT-6.1 Terra, a fast, efficient model for detailed visual reasoning, precise computer use and clearer writing, with standard API prices 50% lower than GPT-5.6 Terra and GPT-6.1 Sol. It is available in ChatGPT Work and Codex for Plus, Pro, Enterprise and Edu, and in the API as gpt-6.1-terra at $1 / $0.05 cached / $5 per million input, cached-input and output tokens.
OpenAI and Google Cloud are bringing OpenAI frontier models and Codex workflows to Gemini's Model Garden, available through Google Cloud Marketplace. According to The Decoder, GPT-6 Astra, GPT-6.1 Sol and GPT-6 Luna launch as a private preview for enterprise customers, making Google Cloud the first major cloud to offer Gemini, Claude and OpenAI models together.
OpenAI introduced two evaluations for low-resource programming languages: MultiLangBench, which asks a model to build a SQLite-compatible database engine in each of 20 languages, and a COBOL migration test that requires byte-for-byte output parity after porting programs to C++, Java, Kotlin, Python or Rust. OpenAI says GPT-6 Astra averaged an 87.4% test pass rate on MultiLangBench, up from 26.8% for GPT-5.6 Sol, and GPT-6.1 Sol reached 86.6% on COBOL migration at low reasoning effort and 97.9% at higher effort, versus 5.4% for GPT-5.6 Sol. It is releasing the MultiLangBench setup and test suite on GitHub. The results are OpenAI's own.
TestingCatalog reports that three model references, aurora-red-alpha, aurora-green-alpha and aurora-blue-alpha, briefly appeared in OpenAI's API and were removed shortly after, then turned up generating images in blind Arena tests. LuminaBench says it tried the red and green variants in Arena and got cat portraits from both; both outlets guess this could be GPT-Image-3, which they say is speculation. OpenAI has not confirmed the models.