LLM Routing in Production: Implementation Guide for Dev Teams

Every request your team sends to a frontier model that a small model could handle is money leaving the budget. RouteLLM-style evaluations show routing can cut costs 40-85% while keeping roughly 95% of frontier quality — but only when it is implemented with discipline, not as a script that guesses.

This is the production implementation guide: classification, decision trees, fallbacks, and the metrics that tell you whether routing is working. It draws on the LLM routing formula post and the LayerFlow routing approach; pricing covers the infrastructure.

Step 1: Classify tasks into tiers

• Tier 1 simple: extraction, formatting, classification, FAQ — small models handle these.
• Tier 2 standard: code review, summarization, structured generation — mid-tier models.
• Tier 3 complex: architecture, deep reasoning, high-stakes output — frontier models.

Classify by the task's requirements, not by snobery. Most teams find 60-80% of their requests land in tier 1 — and were previously all routed to the most expensive model available.

Step 2: Choose the routing strategy

• Rule-based: map task types to tier/model in code. Fast, predictable, cheap to run.
• LLM-as-router: a small fast model classifies the request, then routes. Handles ambiguity, adds one call.
• Semantic: match requests to historical patterns with embeddings. Improves over time, needs infra.
• Quality-gated: start cheap, escalate on failure. Cheapest guarantee, highest latency.

Start with rule-based for your top three task types. Add LLM-as-router when edge cases multiply. Add quality gating only for the workloads that matter most.

Step 3: The decision tree

Real-time user-facing request? Latency budget under one second? Route to tier 1 or 2. Multi-step reasoning or creative synthesis? Quality threshold high. Consider tier 3. Structured output with strict constraints? Tier 2 usually suffices. Then apply the cost check: is there a cheaper model in the same tier? Route to the cheapest adequate option.

Step 4: Fallbacks and retries

Routing without fallbacks is a single point of failure. Define per tier: if the primary model errors, times out, or returns garbage, route to the next model in the tier, then the tier above. OAIError-style retry with exponential backoff for transient failures. Your gateway should make fallback config, not code.

Step 5: Measure, or routing is vibes

• Cost per task by tier: are simple tasks actually landing on cheap models?
• Quality score by tier: is the cheap model meeting the bar?
• Escalation rate: how often does a routed request need a fallback?
• Latency distribution: are user-facing requests staying in budget?
• Savings vs baseline: what would this workload have cost un-routed?

Internal next steps

Start with The LLM Routing Formula and Model Routing: Cost, Latency, Quality. For fallbacks, read Model Fallback Strategies.

Wire routing with a cost check: sign in to LayerFlow and compare tiers on your real workload. Pricing shows plan limits.

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