GPT-4o is OpenAI's flagship multimodal model with text and image capabilities, featuring a 128K token context window and tool calling support.
| Provider | Input / 1M | Output / 1M | Cached / 1M |
|---|---|---|---|
| $1.25 | $5.00 | - | |
| $1.25 | $5.00 | $0.625 | |
| $2.50 | $10.00 | $1.25 | |
| $2.50 | $10.00 | $1.25 | |
| $2.50 | $10.00 | $1.25 | |
| $2.50 | $10.00 | $1.25 |
Prices updated daily. Last check: Sep 6, 2026
Input, output, and batch rates, plus alternatives, for one provider at a time.
Benchmarks measured Sep 2026. Scores are independent evaluations, not vendor-reported.
GPT-4o suits applications requiring multimodal processing, such as document analysis with visual components, customer support systems that handle both text queries and image uploads, and content creation workflows involving text and image coordination. Its tool calling capabilities make it appropriate for building AI agents that interact with external systems, while the 128K context window supports applications processing lengthy documents or maintaining extended conversation history. The model works well for code generation tasks, technical documentation creation, and scenarios where reliable text and image understanding within a single API call is required.
GPT-4o pricing varies by provider and may include different rates for input and output tokens. Check the pricing table above for current rates across all providers offering GPT-4o access.
GPT-4o excels at multimodal tasks requiring both text and image processing, such as document analysis, content creation with visual elements, and building AI agents with tool calling capabilities. Its 128K context window makes it suitable for applications involving long documents or extended conversations.
GPT-4o is an earlier generation model in OpenAI's GPT family. While it provides solid multimodal capabilities and tool calling support, newer models in the family may offer improved performance, updated knowledge, or additional features. Consider your specific requirements for context length, modality support, and recency when choosing between GPT family models.