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9 pages in this section.
Explains why token budgets cap how much conversation, tool output, and memory an agent can hold.
A first walkthrough of picking a model and reading its context and pricing limits.
Compares the leading frontier-model providers by agent-relevant capabilities and tool-use support.
Explains when running models locally via Ollama suits privacy-sensitive or cost-capped agent projects.
A decision checklist for routing cheap tasks to small models and hard tasks to frontier models.
Ten practices for selecting, budgeting, and swapping models across an agent's lifetime.