Smart Routing for LLMs: Balancing Cost, Speed, and Quality

Smart routing sounds abstract until a product has real traffic. Some requests need the strongest reasoning model available. Some need the lowest latency answer that is still good enough. Some are background jobs where cost matters more than time to first token. A single hard-coded model cannot serve all of those jobs well.

Start with explicit intent

A good router should not pretend every request is the same. Sylica supports explicit model slugs for teams that know exactly what they want and meta-routes for teams that want the gateway to rank candidates according to a strategy. The two modes can live together because the contract is stable.

Cost is directional, not absolute

LLM cost usually splits between input and output tokens. A summarization workload with large input and short output behaves differently from a generation workload with a short prompt and long answer. Sylica keeps input and output rates in the model catalog so the system can estimate cost before dispatch and record true cost after usage is known.

Speed is more than model size

Latency depends on provider health, model load, context size, streaming behavior, and network path. The first version of a fast route can use catalog heuristics such as mini, nano, flash, fast, and haiku variants. Over time, production request data can refine the route using real time to first byte and total latency.

The router should be explainable

When something goes wrong, engineers need to know why a model was selected. The gateway should record the requested slug, chosen slug, provider, status, latency, tokens, and cost. Explainable routing is what turns model choice from a mystery into an operational system.