GPT-5.5
OpenAI
At a glance
- Price per 1M tokens (input)
- $5.00
- Price per 1M tokens (output)
- $30.00
- Context
- 1,050,000 tokens
- Free access
- yes (see below)
Refreshed daily; data verified August 15, 2026. Published August 12, 2026.
The GPT-5.5 model is designed for businesses and organizations that require advanced language understanding and generation capabilities. This model is well-suited for tasks that involve image understanding, step-by-step reasoning, and tool calling, which refers to the ability to call external functions or tools to perform specific tasks. The vendor's approach to developing this model focuses on creating a robust and flexible architecture that can be applied to a wide range of applications. By leveraging this model, businesses can automate complex tasks, improve customer engagement, and gain valuable insights from unstructured data. The model's capabilities make it an ideal choice for applications that require a deep understanding of language and visual content.
Specifications & pricing
| Input (per 1M tokens) | $5.00 |
|---|---|
| Output (per 1M tokens) | $30.00 |
| Cache read (per 1M tokens) | $0.50 |
| Context window | 1,050,000 tokens |
| Max output | 128,000 tokens |
| Capabilities | images, tool calling, reasoning |
LiteLLM community dataset (MIT), verified August 15, 2026. Official OpenAI pricing.
What GPT-5.5 would cost on your workload — run it through the cost calculator →
Where to try GPT-5.5 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 understanding and generating human-like language, as well as tasks that require image understanding and step-by-step reasoning.
How do I get started with this model+
To get started with this model, you will need to integrate it into your application or workflow, which may involve working with the vendor's development team or using pre-built APIs and software development kits.
How does this model differ from other models in the line+
This model differs from other models in the line in its ability to understand and generate language in a more nuanced and context-dependent way, as well as its ability to call external tools and functions to perform specific tasks.
What are the limitations of this model+
The limitations of this model include its potential difficulty in understanding certain types of language or images, as well as its reliance on high-quality training data to produce accurate results.
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