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What Is GPT-5.5?
GPT-5.5 is a large language model made by OpenAI. It is the direct successor to GPT-5.4 and part of the GPT model family that powers ChatGPT. Internally, OpenAI referred to it by the codename Spud during development. The model completed pretraining in March 2026 and launched shortly after.
OpenAI was founded in 2015 by Sam Altman, Elon Musk, and others. The company is best known for ChatGPT, which became the fastest-growing consumer app in history after launching in late 2022. GPT-5.5 continues the line of models that started with GPT-1 in 2018 and has evolved through GPT-2, GPT-3, GPT-4, and GPT-5.
The biggest architectural change in GPT-5.5 is native multimodality. Previous GPT models processed images, audio, and video through separate subsystems. GPT-5.5 handles all four modalities in a single forward pass, which makes cross-modal reasoning faster and more coherent.
GPT-5.5 Technical Details
The context window has been expanded significantly. GPT-5 shipped with 128K tokens, and GPT-5.5 pushes this to at least 256K, with some API configurations supporting up to 512K. For practical use, this means entire codebases, long legal contracts, or book-length documents can fit in a single conversation without truncation.
GPT-5.5 is a proprietary model distributed by OpenAI through its API and ChatGPT. Like other GPT models, it is not open-source and cannot be self-hosted. Third-party platforms like Overchat AI provide access to it alongside competing models such as Claude Opus 4.6, Gemini 3 Pro, and DeepSeek V3.2.
In terms of reasoning accuracy, GPT-5.5 shows meaningful gains over GPT-5.4 on standard benchmarks. It is also noticeably better at multi-step tool use, which is the specific capability that agentic frameworks depend on. For everyday users, the difference shows up as fewer factual errors, better code generation, and more natural handling of complex multi-turn conversations.
OpenAI positions GPT-5.5 as the backbone of its unified platform strategy, where ChatGPT, Codex, deep research, and agent capabilities all run on a single model. For developers, this means one API endpoint covers use cases that previously required switching between different specialized models.
