OpenAI: GPT-6 Sol Pro

GPT-6 Sol Pro is a text model from OpenAI. It shares its underlying model with GPT-6 Sol, but it is served with reasoning mode set to pro, which is aimed at higher quality responses on complex tasks. The provider released it on 22 September 2026. If you already know GPT-6 Sol, the practical difference here is the reasoning configuration rather than a different base model.

The model accepts text, images and files as input, and it returns text. Its context window is 1,050,000 tokens, which is large enough to hold very long documents, whole codebases or extended conversation histories in a single request. The maximum output is 128,000 tokens, so long generations are possible when a task calls for them. Because inputs can include images and files alongside text, you can send mixed material in one call rather than converting everything to plain text first.

Those capabilities point to work where the input is large and the reasoning is hard. Long document analysis, such as reviewing contracts, specifications or research papers, fits the context window and the file input. Image input supports tasks like reading charts, diagrams or screenshots together with related text. The pro reasoning mode suits multi step problems, careful planning, structured extraction from messy sources and agent style workflows where the model has to decide what to do next. The large output ceiling helps when the answer itself is long, for example a detailed report or a substantial refactor.

You call the model through api14's OpenAI-compatible API using the model id openai/gpt-6-sol-pro. Requests follow the usual chat completions shape, so existing OpenAI client libraries work with a changed base URL and model id. 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. Tool calling and structured outputs are both available, which makes the model usable in pipelines that need function calls or schema conforming JSON. The reasoning and reasoning_effort parameters let you control how much reasoning work is done, and verbosity and include_reasoning shape what comes back.

One thing to keep in mind is that pro mode spends far more than the standard configuration, so it is best reserved for tasks that actually need the extra reasoning quality. For simpler requests, the non pro GPT-6 Sol variant is likely the more sensible choice. The model outputs text only, so if you need audio or video output, look elsewhere.