You can use generated results for commercial purposes. You own all rights to the content you create. The only restriction: make sure your prompt does not include copyrighted third-party material. You are responsible for respecting the rights to any input data.

gpt-5.4 works with text, documents, and images: it analyzes voluminous files, writes and edits code, solves logic and STEM problems, and prepares analytics and summaries. The context window is 1,050,000 tokens, so a large codebase or a collection of documents fits into a single dialogue.

In a single response, the model outputs up to 128,000 tokens—that's dozens of pages. It's enough for a detailed technical document, an extensive analysis, or an entire code module without breaking it into pieces. If there is more material, simply continue the generation with the next request in the same dialogue.

Yes, the reasoning mode is confirmed: before answering, the model builds an internal chain of steps, checks intermediate conclusions, and only then formulates the result. This is especially noticeable in mathematics, logic problems, analyzing third-party code, and multi-step document analysis, where accuracy is more important than speed.

Yes. The model supports function calling and structured output in JSON format, making it easy to integrate into agents, chatbots, and internal services. In BotHub, everything works through a unified OpenAI-compatible API, so you can change the model without rewriting the integration.

Images and documents are accepted as input: upload a screenshot, diagram, table, or PDF and ask to analyze the content. There is no note in our data about audio and video processing, so it is better to test this scenario on your task before implementation.

We do not have data on supported languages, so it is most reliable to run a couple of test queries on your material and see the result. The BotHub service itself is Russian-speaking: payment with Russian cards in rubles, access without VPN and a foreign card.