LLM routing is the practice of directing each API request to the best-fit language model based on task requirements, cost constraints, and performance goals.
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LLM routing is the process of automatically selecting which large language model should handle a given request based on predefined rules or learned heuristics. Instead of hard-coding a single model for all requests, a routing layer inspects each query and directs it to the model that best matches the task's requirements for quality, speed, and cost. Routing is the foundational capability that enables multi-model AI architectures.
Cost-based routing sends requests to the cheapest model that meets a minimum quality threshold, minimizing spend on simple tasks. Latency-based routing prioritizes the fastest model, which is critical for real-time features like code completion and chat. Quality-based routing selects the most capable model regardless of cost, suitable for high-stakes outputs. Round-robin distributes load evenly across models to avoid rate limits. Most production systems combine these strategies with task-type classification.
A routing layer sits between your application and the model providers. When a request arrives, the router classifies the task (code, creative writing, translation, etc.) and evaluates constraints (latency budget, cost limit, required capabilities like vision). It then selects the optimal model and forwards the request. LLMWise Auto mode implements this as a zero-latency heuristic router that classifies queries via regex patterns and maps them to the best model among 30+ options including GPT-5.2, Claude Sonnet 4.5, and Gemini 3 Flash.
Routing sends each request to exactly one model. Orchestration goes further by involving multiple models in a single request: comparing outputs side by side, blending responses from several models into one, or having one model judge another's output. LLMWise supports both: Auto mode handles routing, while Compare, Blend, Judge, and Mesh modes provide full orchestration. For many applications, starting with simple routing and graduating to orchestration as needs grow is the most practical path.
LLMWise gives you five orchestration modes — Chat, Compare, Blend, Judge, and Mesh — with built-in optimization policy, failover routing, and replay lab. No monthly subscription is required and paid credits do not expire.
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