GPT-4o mini Batch
Neural Network
OpenAI's GPT-4o mini in batch mode: accepts text and images, text output, GPT-4o mini API for bulk tasks.
Specifications
- Input
- text, images, documents
- Output
- text
- Context size
- 128 000 tokens
- Max answer length
- 16 384 tokens
- Capabilities
- function calling
Prompt cost
(per 1M tokens)
Answer cost
(per 1M tokens)
How it works GPT-4o mini Batch?
GPT-4o mini is a compact OpenAI model released after GPT-4o: it accepts text and images as input and provides text output. The batch mode build is designed for scenarios where it is more convenient to send requests in batches and retrieve responses asynchronously, rather than calling the model one by one. Through BotHub, it is accessible from Russia without a VPN or foreign card; payment is made with a Russian card in rubles, based on actual token usage, which does not expire. Over 250 models are available in one window: you can switch to another and compare responses without rewriting the integration, as the API remains OpenAI-compatible. Data is transmitted with AES-GCM encryption and is not stored. For companies, BotHub provides contracts, invoices, and electronic document management with an admin panel and team limits. In practice, the model is used for mass classification of requests and reviews, extracting fields from scans and screenshots, summarizing long conversations, generating uniform catalog descriptions, and background processing of accumulated data.Frequently asked questions about GPT-4o mini Batch
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 as input, and outputs text. It is suitable for bulk data processing: parsing documents and invoices, classifying requests, extracting fields, summarizing, drafting, and code editing. The 128,000-token context allows you to include long files and entire conversations in the request.
The single response limit is 16,384 tokens, which is roughly an average-length article or a large code fragment. If you need a larger result, break the task into parts and pass the previous output back into the request: the 128,000-token window easily accommodates accumulated text.
A separate reasoning mode is not noted in our data. However, you can ask the model to write out the solution steps directly in the prompt — break down the task into points, verify conditions, and explain the output. For complex multi-step logic, it makes sense to compare the result with reasoning models in the same BotHub window.
Yes, both function calling and structured JSON output are supported. The model calls your tools, accesses external services and databases, and returns an answer according to a specified schema. Through the unified OpenAI-compatible BotHub API, this connects to agents and pipelines without rewriting the integration.
Images and documents — yes, including native file processing: screenshots, photos, scans, tables, PDFs. There are no notes in our data regarding audio and video input, so for such tasks, it is better to use a specialized model — you can switch to one in the same interface.
The GPT-4o line of models was trained on multilingual data and works confidently with Russian texts: they understand requests, parse documents, and maintain terminology. It is easy to check the quality with your own task — access from Russia is available without a VPN or foreign card, and payment is in rubles based on actual usage.