GPT 6 Sol Pro
Neural Network
GPT-6 Sol Pro is an OpenAI model with pro reasoning mode: GPT-6 Sol Pro API for complex tasks and multi-step analysis.
Specifications
- Input
- text, images, documents
- Output
- text
- Context size
- 1 050 000 tokens
- Max answer length
- 128 000 tokens
- Reasoning effort
- none, low, medium, high, extra high, max
- Capabilities
- reasoning, function calling
Prompt cost
(per 1M tokens)
Answer cost
(per 1M tokens)
How it works GPT 6 Sol Pro?
GPT-6 Sol Pro is GPT-6 Sol from OpenAI, launched with the reasoning.mode parameter set to 'pro': it's the same base model, but answers to complex tasks are higher quality. The difference from standard GPT-6 Sol is only in the reasoning mode, so you choose the variant based on the task: if a quick answer is enough, use the base version; if step-by-step analysis is needed, use Pro. The batch variant is convenient when requests can be queued and results retrieved later. In BotHub, the model is available from Russia without a VPN or foreign card; payment is made with Russian cards in rubles and charged per token, without a subscription. Over 250 models are available in the same window, and a unified OpenAI-compatible API allows you to switch models without rewriting the integration; data is transmitted with AES-GCM encryption and not stored, while companies can work under a contract with invoices, electronic document management (EDO), and an admin panel with limits. Choose Pro to debug complex issues, refactor code, complete mathematical and engineering calculations, verify the logic of long documents, prepare analytical reviews, and assemble multi-step data processing scenarios.Frequently asked questions about GPT 6 Sol 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.
The model works with text, images, and documents, reasons before answering, and can call functions. It is suitable for analyzing large documents, working with code — writing, refactoring, and debugging — as well as for STEM tasks and analytics where a long chain of reasoning is needed.
Up to 128,000 tokens in a single response — enough for voluminous technical text, a large code module, or a detailed analysis. The context window is 1,050,000 tokens, so you can pass entire source code and documentation and get an answer without losing details.
Yes, reasoning before answering is confirmed by our data. The model builds a train of thought before providing a result, which is noticeable in mathematics, logic, multi-step debugging, and tasks where it is important not to guess the answer but to derive it sequentially.
Yes, function calling and structured JSON output are supported. You connect the model to your services and receive an answer according to a specified schema. In BotHub, this is a unified OpenAI-compatible API, so you can switch to another model without rewriting the integration.
Images and documents can be sent as input along with text: screenshots, diagrams, reports, multi-page files. Audio and video are not noted in our data. Image generation is also not claimed for this model — there are separate solutions for that in the catalog.
The model's working language is not specified in our data, so it is better to check accuracy in Russian with your own tasks — this takes a couple of requests. Access to BotHub is completely Russian: no VPN or foreign card required, payment in rubles per token.