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The model prioritizes responsiveness and efficiency over deep reasoning, making it ideal for pipelines that require fast, reliable outputs at scale. GPT-5.4 nano is well suited for background tasks, real-time systems, and distributed agent architectures where minimizing cost and latency is essential. You can interact with the OpenAI GPT-5.4-nano model through various programming languages and methods. Below are examples showing how to use the model’s API.

API Examples

Generate a model response using the chat endpoint of OpenAI GPT-5.4-nano.

Create chat completion

The Chat Completions API endpoint will generate a model response from a list of messages comprising a conversation.

Default

Streaming

Image Input

Functions

Python

Create a model response

OpenAI’s most advanced interface for generating model responses. Supports text and image inputs, and text outputs. Create stateful interactions with the model, using the output of previous responses as input. Extend the model’s capabilities with built-in tools for file search, web search, computer use, and more. Allow the model access to external systems and data using function calling.

Default

Streaming

Reasoning

Functions

Image Input

File Input