Multi-Model Configuration
goose supports several approaches for using different models within a single session, allowing you to optimize for cost, performance, and task specialization. Strategies range from manual or turn-based model selection to dynamic, context-aware switching.
📚 Documentation & Guides
Switching Models Mid-Session
Use the /model command to change models without losing your session, keeping the same provider or switching to another.
Subagents
Delegate focused tasks to isolated goose instances, each able to run its own provider and model.
Context Engineering
Shape what goose keeps in context across a session, including compaction and persistent instructions.
📝 Featured Blog Posts
Treating LLMs Like Tools in a Toolbox: A Multi-Model Approach to Smarter AI Agents
LLMs are specialized tools, and multi-model approaches create smarter, more efficient AI agents.
The AI Skeptic's Guide to Context Windows
Learn practical ways to manage context windows and token usage in long-running sessions.