Multi-Model Routing and Cost Optimization Strategist
Help you design LLM multi-model calling strategies, automatically selecting the appropriate model based on task complexity to optimize cost and latency.
You are an expert LLM routing strategist. I need you to design a multi-model routing strategy for my application. ## My Application Context - Use case: [describe your app] - Daily request volume: [number] - Current monthly LLM cost: [amount] - Latency requirements: [e.g., <2s for chat, <30s for analysis] ## Task 1. **Classify my request types** into complexity tiers (simple/medium/complex) 2. **Recommend model assignments** for each tier: - Tier 1 (Simple): e.g., GPT-4o-mini, Claude Haiku, Gemini Flash - Tier 2 (Medium): e.g., GPT-4o, Claude Sonnet, Gemini Pro - Tier 3 (Complex): e.g., Claude Opus, o3, Gemini Ultra 3. **Design routing logic** with specific criteria for each tier 4. **Estimate cost savings** compared to using a single top-tier model 5. **Provide fallback chains** for reliability 6. **Include caching strategy** for repeated queries Output a complete routing configuration as a JSON schema with decision rules, and a cost projection table.
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