GPT 5 Nano Batch
Neural Network
GPT 5 Nano is a fast, compact model from OpenAI's GPT-5 line, a GPT 5 Nano API for low-latency tasks.
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 Nano Batch?
GPT 5 Nano is the most compact and fastest option in OpenAI's GPT-5 system. It is designed for developer tools, short interactive exchanges, and environments where minimal latency is critical; while less deep in reasoning than larger GPT-5 versions, it responds faster. The batch variant is intended for batch processing, where requests are sent in arrays rather than individually. In BotHub, the model is available from Russia without a VPN or foreign card, with payment via Russian cards in rubles on a pay-per-token basis, with no subscription required. Over 250 other neural networks are available in one window, and a unified OpenAI-compatible API allows switching to a larger model without rewriting the integration. Requests are encrypted via AES-GCM, data is not stored, and companies have access to contracts, invoices, electronic document management, and an admin panel with limits. Use it for code completion, classifying and labeling large text arrays, batch field extraction from documents, quick support bot responses, and auxiliary steps in multi-agent scenarios where a stronger model forms the final result.Frequently asked questions about GPT 5 Nano 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-nano:batch is a compact OpenAI model in batch mode: it accepts text, images, and documents, reasons before answering, and calls functions. It is suitable for mass repetitive tasks—classification, data extraction, summarization, labeling, and processing large sets of files when the result is not needed instantly.
The output limit is 128,000 tokens per response, which is enough for a voluminous document, a detailed report, or a long series of repetitive results. The context window is 400,000 tokens, so source materials can be passed in their entirety without splitting the task into parts.
Yes, according to our data, the reasoning mode is supported: the model first builds a solution path and then provides an answer. This significantly helps with tasks involving logic, calculations, and multi-step instructions, where it is important not just to continue the text, but to consistently analyze the condition.
Yes, both function calling and structured JSON output are supported. The model can be connected to your tools and databases, and answers can be received in a specified schema. In BotHub, this is available via a unified OpenAI-compatible API, so switching between models does not require rewriting the integration.
According to our data, in addition to text, images and documents are accepted as input: you can send a screenshot, diagram, PDF, or contract and get an analysis, summary, or extracted fields. Audio and video support is not noted in our data, and file generation is not claimed.
We do not have exact data on languages, so we will not make any promises—it is better to check with your own task. In BotHub, this takes a couple of minutes: access from Russia without a VPN or foreign card, payment in rubles per token, no subscription required.