OpenAI: GPT-6 Astra

GPT-6 Astra is OpenAI's flagship text model, released on 4 September 2026. It sits in the text category and is positioned by OpenAI for demanding end-to-end work, with stated strengths in long-horizon tasks. If you are choosing a model for serious analysis or engineering work rather than lightweight chat, this is the tier OpenAI intends you to consider first.

The model accepts text, images and files as input, and returns text only. Its context window is 1,050,000 tokens, and the maximum output is 128,000 tokens. That combination matters for two reasons: you can supply very large inputs (long documents, whole repositories of files, or images alongside text) in a single request, and you can still ask for a substantial response rather than a short summary. Reasoning behaviour is exposed through parameters rather than being fixed, so you control how much internal deliberation the model applies.

Those capabilities point to a fairly specific set of use cases. Advanced analysis over large corpora, software engineering tasks where the model needs to hold a lot of code and context at once, deep research that spans many documents, scientific work, and document creation are the areas OpenAI names. The file and image inputs make it practical to hand over source material directly instead of pre-processing it into text yourself. The large output ceiling suits tasks where the deliverable is itself long, such as a full report or a generated document, rather than a single answer.

You call it through api14's OpenAI-compatible API using the model id "openai/gpt-6-astra". The supported request parameters are include_reasoning, max_completion_tokens, max_tokens, reasoning, reasoning_effort, response_format, seed, structured_outputs, tool_choice, tools and verbosity. In practice that means you can enable or inspect reasoning, tune reasoning_effort and verbosity, cap output with either token limit parameter, request structured or schema-constrained output via response_format and structured_outputs, make sampling reproducible with seed, and give the model tools with tool_choice controlling whether and how they are used. Because the interface is OpenAI-compatible, existing OpenAI SDK code generally works with a base URL and model id change.

One thing to weigh is that this is a text-output model. If your task needs image, audio or video generation, another model will fit better. The same applies if you only need short, cheap, high-volume responses, where a smaller model is likely the more sensible default. GPT-6 Astra is aimed at work where the input is large, the reasoning is non-trivial, or the output is long enough that the 128,000 token ceiling is genuinely useful.