GPT-3.5 Turbo
OpenAI
At a glance
- Price per 1M tokens (input)
- $0.50
- Price per 1M tokens (output)
- $1.50
- Context
- 16,385 tokens
- Free access
- yes (see below)
Refreshed daily; data verified August 15, 2026. Published August 12, 2026.
The GPT-3.5 Turbo model is suitable for businesses and organizations that require advanced natural language processing capabilities. This model is particularly well-suited for tasks that involve generating human-like text, such as writing articles, creating content, and responding to customer inquiries. The vendor's approach to developing this model focuses on enabling tool calling, which allows the model to call external functions and integrate with other systems, making it a versatile tool for a wide range of applications. By leveraging this capability, users can extend the model's functionality and create custom solutions tailored to their specific needs. The model's design prioritizes flexibility and adaptability, making it an attractive option for businesses seeking to automate complex language-based tasks.
Specifications & pricing
| Input (per 1M tokens) | $0.50 |
|---|---|
| Output (per 1M tokens) | $1.50 |
| Context window | 16,385 tokens |
| Max output | 4,096 tokens |
| Capabilities | tool calling |
LiteLLM community dataset (MIT), verified August 15, 2026. Official OpenAI pricing.
What GPT-3.5 Turbo would cost on your workload — run it through the cost calculator →
Where to try GPT-3.5 Turbo 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 the primary use case for the GPT-3.5 Turbo model+
The GPT-3.5 Turbo model is primarily used for generating high-quality, human-like text, making it suitable for applications such as content creation, article writing, and customer response generation
How do I get started with using the GPT-3.5 Turbo model+
To get started with the GPT-3.5 Turbo model, users can begin by familiarizing themselves with the model's capabilities and limitations, and then experiment with using the model to generate text for their specific use case
How does the GPT-3.5 Turbo model differ from other models in the line+
The GPT-3.5 Turbo model differs from other models in the line in its ability to perform tool calling, which enables it to call external functions and integrate with other systems, making it a more versatile and adaptable option
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