Model

A model is a trained AI system that generates content from the context it receives. In agent systems, it consumes context items, such as instructions, user messages, and tool outputs, and produces new items, such as model answers and tool calls.

Most modern language models use the Transformer architecture. Their capabilities determine which context items they can consume and produce, and how those items are delivered:

• Tool calling enables the model to produce tool call items containing a function name and arguments.
• Reasoning enables the model to work through a problem before producing an answer or tool call. Providers may expose reasoning items or summaries. Some models offer reasoning effort settings to control how much computation they spend reasoning.
• Streaming delivers generated context items incrementally, before the entire response is complete.
• Structured output constrains the content of a model answer to a defined schema, such as a JSON structure.

Model usage distinguishes input tokens, representing the context processed, from output tokens, representing the content generated, including reasoning tokens where applicable. Provider API pricing is mainly based on the number of input and output tokens used, usually with separate rates for each.