GPT-4
Neural Network
OpenAI's GPT-4 is a multimodal language model with advanced reasoning for complex tasks and coding.
Specifications
- Input
- text, images, documents
- Output
- text
- Context size
- 8 191 tokens
- Max answer length
- 4 096 tokens
- Capabilities
- function calling
Prompt cost
(per 1M tokens)
Answer cost
(per 1M tokens)
How it works GPT-4?
GPT-4 is OpenAI's flagship model: a large multimodal language system that handles complex tasks more accurately than previous models due to broader general knowledge and advanced reasoning. It is a versatile tool for text and code when reasoning accuracy is critical. In BotHub, GPT-4 is accessible from Russia without a VPN or foreign card; payment is made in rubles via Russian cards, based on actual token usage without a subscription. Over 250 models are available in one window: you can compare responses and switch models without rewriting your integration, as a unified OpenAI-compatible API serves them via a common protocol. Chats are encrypted and not saved. Companies have access to contracts, invoices, electronic document management, and an admin panel with limits. It is useful for analyzing technical documentation, writing and debugging code, preparing analytical summaries from large materials, solving math and STEM problems with step-by-step breakdowns, and proofreading work documents.Frequently asked questions about GPT-4
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-4 works with text: it writes and edits materials, analyzes code, and helps with analysis and reasoning. You can input not only text but also documents with images. The context is 8191 tokens, which is enough for emails, articles, briefs, and code snippet analysis.
The model generates up to 4096 tokens per response. The total window is 8191 tokens, shared between your request and the response, so the longer the source materials, the less space remains for text. It is more convenient to generate large documents in parts, section by section.
A separate reasoning mode is not specified in our data, so do not expect a visible chain of thought. However, you can explicitly ask in the prompt to break down the task step-by-step, and the model will detail the logic in its response. This works for complex analyses.
Yes, function calling and structured JSON output are supported. You describe the tools, the model decides which one to call, and returns arguments in the specified format. In BotHub, this is available via a unified OpenAI-compatible API, so you can switch to another model without rewriting your integration.
You can upload images and documents: the model will analyze the image, diagram, or file and respond with text. Audio and video are not listed among supported input formats; there are specialized models in the catalog for those. GPT-4's response is always text — it does not generate images.
Language-specific characteristics are not specified in our data, so we cannot promise exact performance. OpenAI's GPT-4 is known as a multilingual model, and the easiest way is to test it on your task — in BotHub, access is open without a VPN or foreign card, and payment is in rubles.