GPT 5.4 Nano Batch
Neural Network
GPT 5.4 Nano is a lightweight OpenAI model from the GPT-5.4 family for fast, high-load tasks with text and images.
Specifications
- Input
- text, images, documents
- Output
- text
- Context size
- 400 000 tokens
- Max answer length
- 128 000 tokens
- Reasoning effort
- none, low, medium, high, extra high
- Capabilities
- reasoning, function calling
Prompt cost
(per 1M tokens)
Answer cost
(per 1M tokens)
How it works GPT 5.4 Nano Batch?
GPT 5.4 Nano is the lightest and most cost-effective model in the OpenAI GPT-5.4 family, designed for low latency and high request volume. It accepts text and images as input, and the batch variant is designed for processing large volumes. In BotHub, it is available without a VPN or foreign card: pay with Russian cards per token, no subscription, and the balance does not expire. Here, in one window, there are over 250 neural networks, making it easy to compare models, and a unified OpenAI-compatible API allows switching between them without rewriting integrations; traffic is encrypted, and for companies, there is a contract, invoice, EDI, and admin panel with limits. The model is suitable for high-volume tasks: classifying and labeling requests, extracting fields from documents and screenshots, suggestions and autocomplete directly in the product interface, and rough parsing of code and logs before passing the task to a heavier model. Batch mode is useful for background runs on large datasets.Frequently asked questions about GPT 5.4 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.
This is a text model that accepts images and documents as input. It is suitable for file analysis, data extraction, coding, reasoning, and STEM tasks, as well as function calling scenarios. The batch variant is convenient when you need to process a large volume of similar requests.
In a single response, the model outputs up to 128,000 tokens — enough for a voluminous document, long code analysis, or a detailed report. The total context window is 400,000 tokens, which accommodates both your request with files and the response itself.
Yes, the reasoning mode is confirmed: before answering, the model can break down the task into steps, check intermediate conclusions, and only then formulate the result. This significantly helps with mathematics, logic, code debugging, and tasks where accuracy is more important than speed.
Yes, the model supports function calling and structured JSON output. You can describe the response schema and receive predictable fields for a database or interface, as well as connect external tools and APIs. Through the unified OpenAI-compatible BotHub API, this works without rewriting integrations.
According to our data, it accepts text, images, and documents as input: screenshots, diagrams, scans, PDFs, and other files can be parsed directly in the chat. We have no confirmation of audio or video input support. The model responds with text. For audio and video, BotHub has separate models.
We do not have data on the quality of performance with specific languages, so we cannot make any promises — please test it with your task. It is fast: in BotHub, the model is available from Russia without a VPN or foreign card, payment is in rubles, and you can compare answers from other models in the same window.