GPT-4o 2024-05-13
Neural Network
OpenAI's GPT-4o: accepts text and images, outputs text. GPT-4o for coding, analysis, and complex reasoning.
Max answer length
(in tokens)
Context size
(in tokens)
Prompt cost
(per 1M tokens)
Answer cost
(per 1M tokens)
How it works GPT-4o 2024-05-13?
GPT-4o is OpenAI's multimodal model: it accepts text and images as input and outputs text, maintaining GPT-4 Turbo intelligence at higher speeds. The 2024-05-13 version is a fixed snapshot: model behavior remains constant, which is crucial for workflows. In BotHub, this model is available without VPN or foreign cards; payment is in rubles via Russian cards, charged per used token, which never expire. Over 250 models are available in the same window, allowing easy switching and comparison. A unified OpenAI-compatible API lets you swap models without rewriting integrations. Chats are encrypted via AES-GCM. For companies, we offer contracts, invoices, electronic document management, and an admin panel with limits. Developers can use it to analyze code, write functions, and debug logs. Analysts can extract insights from charts and tables. Marketers can generate and iterate on copy. Students and researchers can solve step-by-step math and science problems.Frequently asked questions about GPT-4o 2024-05-13
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 versatile OpenAI text model: analyzing long documents, writing and refactoring code, debugging, analytics, STEM tasks, and preparing structured data. The 128,000-token context allows you to keep large projects, correspondence, or technical documentation in a single dialogue without losing details.
The model outputs up to 4096 tokens per response, which is several pages of text. If you need more, break the task into parts and ask it to continue: the 128,000-token context will retain everything written previously, ensuring the continuation remains coherent.
A separate reasoning mode is not specified in our data; the response is generated immediately. However, step-by-step analysis is available via prompting: ask it to reason step-by-step, verify the solution process, and show intermediate conclusions, which significantly improves accuracy on complex tasks.
Yes, both function calling and structured JSON output are supported. This makes it easy to integrate the model into agents, chatbots, and business logic. In BotHub, it works via a unified OpenAI-compatible API, so switching models does not require rewriting integrations.
In addition to text, it accepts images and documents: send a screenshot, diagram, table, or file and get a text analysis. Audio and video are not supported in our data; for such tasks, BotHub has separate models available in the same window.
The model works confidently with Russian: it accurately maintains terminology, style, and meaning, and analyzes long Russian-language documents and code comments. No special settings are needed—formulate your request as usual and specify the desired format and length of the response.