GPT 5.4 Mini Batch
Neural Network
GPT 5.4 Mini by OpenAI is a fast model for reasoning and code; gpt 5.4 mini api for batch processing of large request volumes.
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 Mini Batch?
GPT 5.4 Mini is a lightweight OpenAI model that brings core GPT 5.4 capabilities into a faster, more cost-effective form, designed for high-volume streaming workloads. It accepts text and images, handles reasoning and programming tasks confidently, and the batch variant is designed for bulk processing where tasks are sent as an array and results are retrieved as they become ready. In BotHub, the model is accessible from Russia without a VPN or foreign card: payment is made with Russian cards in rubles based on actual token usage, and tokens do not expire. Over 250 other neural networks are available in the same window, allowing you to compare responses or switch models without rewriting your integration—the API is OpenAI-compatible, and chats are encrypted with AES-GCM. For teams, we offer contracts, invoices, electronic document management (EDO), and an admin panel with limits. Simple scenarios include: mass text labeling and classification, parsing screenshots and scans, code generation and refactoring with debugging, high-load assistant support, and overnight analytics runs on accumulated data.Frequently asked questions about GPT 5.4 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.
It is a text model with reasoning capabilities: it parses documents and images, writes and edits code, prepares analytics, and answers complex questions. A 400,000-token context allows you to work with large sets of files, and function calling integrates it into your services and batch scenarios.
Up to 128,000 tokens in a single response—the volume of a small book. Enough for long technical text, translating a large document, detailed code analysis, or a complete structured report, without manually splitting tasks into parts and gluing them back together.
Yes, a reasoning mode is specified in the characteristics: before answering, the model breaks the task down into steps. This is noticeable in math, logic, code analysis, and multi-step instructions—where the correct train of thought and verifiable result are more important than the fastest response time.
Yes, both are supported. The model calls your functions and tools, and can return responses strictly according to a specified JSON schema, which is easy to parse on the backend. In BotHub, this works via a unified OpenAI-compatible API, common to all models.
Images and documents—yes, they can be sent as input along with text: the model reads screenshots, diagrams, tables, and entire files. Audio and video support is not noted in our data, so for those formats, it is more convenient to switch to a specialized model in the same window.
We do not have specific data on languages, so we cannot promise specific accuracy—it is fairer to test it with your task in a couple of requests. What is guaranteed on our part: access from Russia without a VPN or foreign card, payment in rubles, and billing based on actual token usage.