GPT-4.1
OpenAI
At a glance
- Price per 1M tokens (input)
- $2.00
- Price per 1M tokens (output)
- $8.00
- Context
- 1,047,576 tokens
- Free access
- yes (see below)
Refreshed daily; data verified August 15, 2026. Published August 12, 2026.
The GPT-4.1 model by OpenAI is designed for businesses and organizations that require advanced language understanding and generation capabilities. This model is particularly suited for tasks that involve image understanding and tool calling, which refers to the ability to call external functions or tools to perform specific tasks. The vendor's approach distinguishes itself through its focus on developing a robust and flexible model that can be integrated into a wide range of applications. By leveraging this model, businesses can automate complex tasks and improve their overall efficiency. The model's capabilities make it an ideal choice for companies looking to enhance their language-based systems and workflows.
Specifications & pricing
| Input (per 1M tokens) | $2.00 |
|---|---|
| Output (per 1M tokens) | $8.00 |
| Cache read (per 1M tokens) | $0.50 |
| Context window | 1,047,576 tokens |
| Max output | 32,768 tokens |
| Capabilities | images, tool calling |
LiteLLM community dataset (MIT), verified August 15, 2026. Official OpenAI pricing.
What GPT-4.1 would cost on your workload — run it through the cost calculator →
Where to try GPT-4.1 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 and tool calling, making it suitable for applications such as automated content generation and data processing
How do I get started with this model+
To get started with this model, you will need to integrate it into your existing workflow or application, which may require some development work to set up the necessary interfaces and tools
How does this model differ from other models in the line+
This model differs from other models in the line through its advanced image understanding and tool calling capabilities, which make it more suitable for complex tasks that require external tools or functions
What are the limitations of this model+
The limitations of this model include its reliance on high-quality input data and its potential difficulty in handling very specialized or niche tasks, which may require additional customization or fine-tuning
Comparisons
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