GPT-5 Mini Batch
Neural Network
GPT-5 Mini API is a compact version of OpenAI's GPT-5 for light reasoning tasks with lower response latency.
Specifications
- Input
- text, images, documents
- Output
- text
- Context size
- 400 000 tokens
- Max answer length
- 128 000 tokens
- Reasoning effort
- minimal, low, medium, high
- Capabilities
- reasoning, function calling
Prompt cost
(per 1M tokens)
Answer cost
(per 1M tokens)
How it works GPT-5 Mini Batch?
GPT-5 Mini is a compact version of OpenAI's GPT-5 for tasks that don't require the full reasoning power of the larger model: it offers the same instruction following and safety settings but responds faster and costs less. The batch variant is designed for bulk processing, where requests are sent in arrays and an immediate response isn't required. Through BotHub, the model is accessible without a VPN or foreign card: pay with a Russian card in rubles for tokens used, which do not expire. Access over 250 neural networks in one window, switch between them in a few clicks, and use a unified OpenAI-compatible API for development, allowing you to swap models without rewriting integrations. Dialogs are encrypted; for companies, we offer contracts, invoices, electronic document management, and an admin panel with limits. Simple use cases: analyzing incoming requests and emails, summarizing long correspondence, drafting standard texts, coding assistance and debugging, and mass processing of similar requests via API.Frequently asked questions about GPT-5 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.
gpt-5-mini:batch accepts text, images, and documents, reasons before answering, and calls external functions. A 400,000-token context allows for analyzing long reports and codebases, and extracting data from scans and tables. The batch mode is convenient when there are many tasks and an immediate response is not required.
Up to 128,000 tokens in a single response—about the size of a small book. This capacity is enough for a detailed document analysis, a large code module, or a series of related sections. If generation hits the limit, ask it to continue in the next message.
Yes, reasoning before answering is confirmed by our data. The model first builds an internal chain of steps and only then provides the result—this is noticeable in tasks involving counting, logic, and multi-step conditions. For simple queries, the speed difference is usually small.
Yes, both. The model calls your functions and returns structured JSON according to a specified schema, making it easy to integrate into agents and workflows. In BotHub, this is available via a unified OpenAI-compatible API—you can replace the model without rewriting the integration.
According to our data, images and documents are accepted as input: send a scan, diagram, table, or the entire file and ask it to analyze the content. Audio and video are not noted in our data, so for audio or video analysis, please select a specialized model from the catalog.
Our data does not specifically track the language of prompts and responses, so it is best to test the model with your typical query. Payment is based on actual token usage, and tokens do not expire. BotHub itself is accessible from Russia without a VPN or foreign card, with payment via Russian cards.