GPT-5.4 Nano
OpenAI
At a glance
- Price per 1M tokens (input)
- $0.20
- Price per 1M tokens (output)
- $1.25
- Context
- 272,000 tokens
- Free access
- yes (see below)
Refreshed daily; data verified August 15, 2026. Published August 9, 2026.
The GPT-5.4 Nano model is designed for businesses and organizations that require a versatile language model for a range of tasks, including image understanding and tool calling, which refers to the ability to call external functions or tools to augment its capabilities. This model is well-suited for applications that involve step-by-step reasoning, such as data analysis or problem-solving. The vendor's approach is distinguished by its emphasis on providing a robust and reliable model that can be easily integrated into existing workflows. By leveraging the model's capabilities, businesses can automate tasks, gain insights from images, and make more informed decisions.
Specifications & pricing
| Input (per 1M tokens) | $0.20 |
|---|---|
| Output (per 1M tokens) | $1.25 |
| Cache read (per 1M tokens) | $0.02 |
| Context window | 272,000 tokens |
| Max output | 128,000 tokens |
| Capabilities | images, tool calling, reasoning |
LiteLLM community dataset (MIT), verified August 15, 2026. Official OpenAI pricing.
What GPT-5.4 Nano would cost on your workload — run it through the cost calculator →
Where to try GPT-5.4 Nano for free
- OpenAI offers a free chat — ChatGPT (free plan). A vendor's free chat may run a different model from the same family — the exact model is not guaranteed.
Frequently asked questions
What is this model good for+
This model is good for tasks that involve image understanding, step-by-step reasoning, and tool calling, making it suitable for applications such as data analysis, problem-solving, and automation of tasks
How do I get started with this model+
To get started with this model, you will need to integrate it into your existing workflow, which may involve setting up an application programming interface or working with a developer to ensure seamless interaction with the model
How does this model differ from other models in the line+
This model differs from other models in the line in its specific capabilities, such as image understanding and tool calling, which set it apart from models that may focus more on text-based tasks
What are the limitations of this model+
The limitations of this model include its potential inability to handle very complex tasks or tasks that require a high degree of nuance or human judgment, which may require additional human oversight or review
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