Directing different agent tasks to different LLM models based on complexity, cost, or speed requirements.
Not every task needs the most powerful (and expensive) model. A simple FAQ lookup works fine with Claude Haiku ($0.25/M tokens). A complex reasoning task needs Claude Sonnet ($3/M tokens). Model routing directs each task to the appropriate model.
This optimizes the cost-quality tradeoff. Simple tasks stay cheap. Complex tasks get the intelligence they need.
LLM costs can spiral without model routing. Running every task on GPT-4 or Claude Opus is expensive. Model routing cuts costs 50-80% without sacrificing quality where it matters.
Clawctl supports BYOK with multiple providers. Configure different models per agent in a multi-agent setup. Use fast models for triage and powerful models for complex reasoning.
Try Clawctl — 60 Second DeployHaiku/GPT-4o-mini for triage, categorization, and simple tasks. Sonnet/GPT-4 for complex reasoning. Opus for the hardest problems.
Yes. Update the model in your openclaw.json or Clawctl dashboard. Takes effect immediately.
Yes. Ollama integration lets you run local models for sensitive or cost-optimized workloads.
BYOK (Bring Your Own Key)
A model where you provide your own LLM API key (Anthropic, OpenAI, etc.) instead of the platform providing one, giving you full cost control and model choice.
Cost Optimization
Strategies for reducing LLM and infrastructure costs when running AI agents without sacrificing quality or reliability.
Context Window
The maximum amount of text an LLM can process in a single request — including the conversation history, system prompt, and tool results.
Multi-Agent Systems
Systems where multiple AI agents collaborate, each with specialized roles, to solve problems more effectively than a single agent.