Model routing configuration templates and strategies for cost optimization, speed optimization, quality optimization, and intelligent fallback chains. Use when building AI applications with OpenRouter, implementing model routing strategies, optimizing API costs, setting up fallback chains, implementing quality-based routing, or when user mentions model routing, cost optimization, fallback strategies, model selection, intelligent routing, or dynamic model switching.
View on GitHubFebruary 1, 2026
Select agents to install to:
npx add-skill https://github.com/vanman2024/ai-dev-marketplace/blob/main/plugins/openrouter/skills/model-routing-patterns/SKILL.md -a claude-code --skill model-routing-patternsInstallation paths:
.claude/skills/model-routing-patterns/# Model Routing Patterns Production-ready model routing configurations and strategies for OpenRouter that optimize for cost, speed, quality, or balanced performance with intelligent fallback chains. ## Purpose This skill provides comprehensive templates, scripts, and strategies for implementing sophisticated model routing in OpenRouter-powered applications. It helps you: - Reduce API costs by routing to cheaper models when appropriate - Optimize for speed with fast models and streaming - Maintain quality with premium model fallbacks - Implement intelligent task-based routing - Build reliable multi-tier fallback chains ## Activation Triggers Use this skill when: - Designing model routing strategies - Implementing cost optimization - Setting up fallback chains for reliability - Building task complexity-based routing - Configuring dynamic model selection - Optimizing API performance vs cost tradeoffs - Implementing A/B testing for models - Setting up monitoring and analytics ## Available Routing Strategies ### 1. Cost-Optimized Routing **Goal:** Minimize API costs while maintaining acceptable quality **Strategy:** - Use free models (google/gemma-2-9b-it:free, meta-llama/llama-3.2-3b-instruct:free) - Fallback to budget models (anthropic/claude-4.5-sonnet, openai/gpt-4o-mini) - Premium models only for complex tasks requiring highest quality **Template:** `templates/cost-optimized-routing.json` **Best for:** - High-volume applications - Simple tasks (classification, extraction, formatting) - Development/testing environments - Budget-constrained projects ### 2. Speed-Optimized Routing **Goal:** Minimize latency and response time **Strategy:** - Prioritize fastest models regardless of cost - Enable streaming for immediate feedback - Use smaller models with quick inference - Geographic routing to nearest endpoints **Template:** `templates/speed-optimized-routing.json` **Best for:** - Real-time chat applications - Interactive user experiences - Low-latency requi