GPT 5.2 Pro
Neural Network
GPT-5.2 Pro: OpenAI model with step-by-step reasoning and agentic coding; GPT 5.2 Pro API for complex multi-step tasks.
Specifications
- Input
- text, images, documents
- Output
- text
- Context size
- 400 000 tokens
- Max answer length
- 128 000 tokens
- Reasoning effort
- medium, high, extra high
- Capabilities
- reasoning, function calling
Prompt cost
(per 1M tokens)
Answer cost
(per 1M tokens)
How it works GPT 5.2 Pro?
GPT-5.2 Pro is an OpenAI model designed for tasks requiring step-by-step analysis: it unfolds reasoning sequentially rather than providing the first answer that comes to mind. Compared to GPT-5 Pro, it features improved agentic coding and long-context handling, allowing it to manage large materials and multi-step scenarios more effectively. In BotHub, it is accessible from Russia without a VPN or foreign card, and you pay only for tokens used, with no subscription and no expiration of remaining balance. Nearby, in the same window, are over 250 models: easily switch between them and compare answers for the same prompt. A unified OpenAI-compatible API allows you to replace the model in a multi-model system without rewriting the integration. Chats are encrypted via AES-GCM and not saved, while companies have access to contracts, invoices, electronic document management, and an admin panel with limits. It is suitable for analyzing large codebases to find bugs, building agentic chains where the model drives tasks to completion, analyzing long documents and reports in their entirety, and verifying engineering or scientific calculations. Batch mode is convenient for running many similar requests at once.Frequently asked questions about GPT 5.2 Pro
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.
This is a text model with a 400,000 token context: it reads large documents and entire codebases, writes and refactors code, finds bugs, and analyzes STEM tasks and analytics. It is suitable for research, working with contracts and reports, and for function calling within your services.
Up to 128,000 tokens in a single response — enough for a voluminous technical document, a large code module, or a detailed analysis of an entire study without manual splitting. If the task is even larger, break it into steps: the 400,000 token context allows you to keep the entire history nearby.
Yes, reasoning before answering is confirmed. The model first breaks down the task step-by-step and then formulates a conclusion — this is noticeable in mathematics, logic, code debugging, and where data from different parts of a long document needs to be compared. For simple questions, this mode is usually redundant.
Yes, both function calling and structured JSON output are supported. The model will return an answer according to a specified schema and select the necessary tool from those you described. Through BotHub's unified OpenAI-compatible API, you can connect it to agents and pipelines without rewriting the integration.
According to our data, images and documents are accepted as input, including native file processing: you can send an interface screenshot, diagram, chart, or PDF and ask to analyze the content. Audio and video input is not noted in our data. The model returns the answer in text.
GPT family models from OpenAI traditionally work confidently with Russian: they understand task formulations, terminology, and conversation context. There are no specific language benchmarks in our data, so it is easier to test it with your own task — in BotHub, access is open from Russia, without a VPN or foreign card, and payment is in rubles.