GPT-4 Turbo

It excels at tasks that require both visual and textual reasoning, such as extracting data from receipts or slides, summarizing documents with embedded images, and building conversational agents that can act on user requests. Its tool calling capability also makes it suitable for automating workflows, like fetching records from a database or sending updates to a CRM, directly from a chat interface.

You access it through OpenAI’s API, where you can send requests with text and image inputs. The API documentation provides examples for enabling tool calling and handling responses. For quick experimentation, you can use OpenAI’s playground environment, then move to a development environment with your own API keys.

GPT-4 Turbo is an earlier iteration that balances strong reasoning with image understanding, while GPT-4o is a newer model with faster response times and enhanced multimodal capabilities. GPT-4 mini is a smaller, more efficient variant designed for simpler tasks at lower latency. GPT-4 Turbo remains a solid choice for applications that need robust performance without the latest optimizations.

It can struggle with highly complex spatial reasoning in images, such as counting objects or reading dense fine print. Its knowledge is not real-time, so it may not know recent events unless you provide context. Tool calling requires careful setup to avoid errors, and the model may occasionally produce plausible-sounding but incorrect outputs, so validation is recommended for critical decisions.