GPT-4.1106 Preview
OpenAI
At a glance
- Price per 1M tokens (input)
- $10.00
- Price per 1M tokens (output)
- $30.00
- Context
- 128,000 tokens
- Free access
- yes (see below)
Refreshed daily; data verified August 15, 2026. Published August 12, 2026.
The GPT-4.1106 Preview model by OpenAI is suitable for businesses and developers who require a robust language model for various tasks, such as text generation, conversation, and data analysis. This model's capability for tool calling, which refers to the ability to invoke external functions or tools to perform specific tasks, sets it apart from other language models. The vendor's approach focuses on providing a flexible and adaptable model that can be fine-tuned for specific use cases, allowing users to tailor the model to their particular needs. As a result, this model is a good fit for applications that require a high degree of customization and integration with external tools and systems. Its flexibility and adaptability make it an attractive choice for businesses looking to leverage the power of language models in their operations.
Specifications & pricing
| Input (per 1M tokens) | $10.00 |
|---|---|
| Output (per 1M tokens) | $30.00 |
| Context window | 128,000 tokens |
| Max output | 4,096 tokens |
| Capabilities | tool calling |
LiteLLM community dataset (MIT), verified August 15, 2026. Official OpenAI pricing.
What GPT-4.1106 Preview would cost on your workload — run it through the cost calculator →
Where to try GPT-4.1106 Preview 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 well-suited for tasks that require the generation of human-like text, such as chatbots, content creation, and language translation, as well as for tasks that involve data analysis and processing
How do I get started with this model+
To get started with this model, users can begin by reviewing the documentation and guidelines provided by the vendor, which outline the steps for integrating the model into their application or system, including setting up the necessary tools and infrastructure for tool calling
How does this model differ from other models in the line+
This model differs from other models in the line in its ability to perform tool calling, which allows it to leverage the capabilities of external tools and systems, providing a more comprehensive and integrated solution for users
What are the limitations of this model+
The limitations of this model include its dependence on the quality and availability of the external tools and systems it invokes, as well as its potential vulnerability to errors or biases in the data it processes or the tools it uses
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