GPT 5.4 Pro Batch
Neural Network
GPT 5.4 Pro is an OpenAI model with enhanced reasoning and over a million tokens of context for complex tasks.
Specifications
- Input
- text, images, documents
- Output
- text
- Context size
- 1 050 000 tokens
- Max answer length
- 128 000 tokens
- Reasoning effort
- medium, high, extra high
- Capabilities
- reasoning, function calling
Prompt cost
(per 1M tokens)
Answer cost
(per 1M tokens)
import OpenAI from 'openai';
const openai = new OpenAI({
apiKey: '<your bothub access token>',
baseURL: 'https://openai.bothub.chat/v1'
});
// Sync - Text generation
async function main() {
const chatCompletion = await openai.chat.completions.create({
messages: [{ role: 'user', content: 'Say this is a test' }],
model: 'gpt-5.4-pro:batch',
});
}
// Async - Text generation
async function main() {
const stream = await openai.chat.completions.create({
messages: [{ role: 'user', content: 'Say this is a test' }],
model: 'gpt-5.4-pro:batch',
stream: true
});
for await (const chunk of stream) {
const part: string | null = chunk.choices[0].delta?.content ?? null;
}
}
main();
How it works GPT 5.4 Pro Batch?
GPT 5.4 Pro continues the OpenAI GPT 5.4 line: the same unified architecture, but with enhanced reasoning for complex and critical tasks where the cost of error is high. A context of over a million tokens allows you to work with voluminous documents, long dialogues, and entire large codebases, while the batch variant is designed for batch request processing, where volume is more important than an instant response. In BotHub, the model works without a VPN or foreign card: you pay with a Russian card as you go, for consumed tokens, without a subscription, and the balance does not expire. Nearby, in one window, there are over 250 models — answers are easy to compare and switch between, and a unified OpenAI-compatible API allows you to change the model in your system without rewriting the integration; data is encrypted, and companies have access to contracts, invoices, electronic document management, and an admin panel with limits. In practice, it is used for analyzing multi-page contracts and reports, auditing and refactoring large repositories, step-by-step breakdowns for mathematics and engineering calculations, mass processing of datasets in batches, and preparing analytical reviews from dozens of sources.Frequently asked questions about GPT 5.4 Pro 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-5.4-pro:batch works with text, images, and documents: it analyzes long reports, writes and refactors code, finds bugs, and solves math and STEM problems. A context of up to 1,050,000 tokens allows you to work with an entire codebase or correspondence archive.
Up to 128,000 tokens in a single response — that's hundreds of pages of text. Enough for a large technical document, a detailed analysis, or a large code module in its entirety, without breaking the task into parts and manually stitching fragments together.
Yes, the reasoning mode is confirmed: the model builds a solution path before the final answer. This is noticeable in multi-step tasks — mathematics, logic, code debugging, and analysis of large documents. The response comes slightly slower, but is more accurate in details and conclusions.
Yes, function calling and structured JSON output are supported — the model is suitable for agents, pipelines, and integrations where the response needs to be parsed by code immediately. Through the unified OpenAI-compatible BotHub API, you can switch to another model without rewriting the integration.
Images and documents — yes: you can send a screenshot, diagram, scan, or PDF and ask to analyze the content. Audio and video input is not noted in our data, so do not count on it in advance — check with your own file or choose a specialized model in BotHub.
The language of prompts and responses is not noted in our data, so we will not make any promises here. The most honest way is to give the model your real request in Russian and compare its answer with another model in the same BotHub window; payment is made on a pay-per-token basis.