LLM Routing
The right model for
every request. Automatically.
Not every request needs GPT-4o. PromptUnit classifies each call across 10 task dimensions and routes it to the cheapest model that still clears your quality bar.
LLM routing is the practice of directing each AI request to the model best suited for it, balancing cost and quality on a per-request basis rather than defaulting every call to the same flagship model. In production, most AI workloads are a mix of simple and complex tasks. Simple tasks (summarization, classification, structured extraction) do not require the same model capability as complex ones (multi-step reasoning, code generation, research synthesis). Routing separates them automatically.
PromptUnit's routing engine classifies each incoming request across 10 signal dimensions: task type, prompt complexity, context length, output format requirements, presence of tool calls, domain specificity, and more. From those signals, it selects the cheapest model in your provider set that has historically met your quality threshold on similar requests. The routing decision takes under 5 milliseconds and is invisible to your application code.
The routing engine improves over time. Each routing decision is logged alongside the quality outcome. After 7 days of traffic, the system recalibrates its per-task model weights based on observed quality signals, retry rates, output length anomalies, and downstream implicit feedback. This means the routing accuracy compounds: a system that has been running for 30 days routes more accurately than one that started yesterday, because it has more signal about which models perform well on your specific traffic mix.
Cross-provider routing extends this further. PromptUnit searches across all connected providers, OpenAI, Anthropic, Google, Groq, DeepSeek, to find the cheapest qualifying model for each task type. A summarization task that costs $0.15 per million tokens on GPT-4o-mini might cost $0.08 on Claude Haiku or $0.06 on Groq's Llama 4 Scout. Cross-provider routing finds those opportunities automatically without requiring any changes to your integration code.
Task classification
Detects summarization, classification, extraction, reasoning, code generation, and more across 10 signal dimensions.
Quality threshold
You set the minimum quality score (0–100). Every routing decision is bounded by it. Accuracy never drops below your bar.
Cross-provider routing
Searches for the cheapest qualifying model across all connected providers, not just within one.
Adaptive learning
Routing improves over time as quality signals accumulate. The system recalibrates weekly based on your actual traffic patterns.
14-day shadow mode
Observe routing decisions and projected savings before enabling anything. No surprises, no production risk.
Override control
Tag any request with a feature flag to keep it on a specific model, regardless of routing logic.
Routing in practice
Your code sends the same request it always has. PromptUnit intercepts it, classifies the task, selects the optimal model, and returns a standard OpenAI-format response. Your application never knows a routing decision was made.
// Your code, unchanged
const response = await openai.chat.completions.create({
model: "gpt-4o",
messages: [{ role: "user", content: "Summarize this article..." }],
});
// PromptUnit routes it to gpt-4o-mini, 94% cheaper
// Response arrives in standard OpenAI format, your app never notices
Who this is for
LLM routing is the right solution for teams that want to reduce AI inference costs without building and maintaining routing logic themselves. Writing a routing layer in-house requires defining task types, maintaining model benchmarks, handling provider changes, and managing quality regressions, typically 2–4 weeks of engineering effort, with ongoing maintenance cost.
PromptUnit's routing engine is pre-built, self-improving, and connected to a live benchmark database that tracks model quality across providers. Teams that integrate PromptUnit get production-grade routing on day one, with accuracy that improves as their own traffic data accumulates.
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Free to start. No routing until you click. Pay only from savings.
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