How I Cut LLM Inference Costs by 78% Without Sacrificing Quality

A production team cut LLM inference costs by adding a complexity-based router instead of sending every request to a 70B model.

Easy prompts were sent to a smaller model, while hard requests still went to the large model, preserving quality.

Monthly spend dropped from $14,200 to $3,100, while P99 latency improved and throughput increased.

The setup used models like Qwen2.5-1.5B-Instruct and Llama-3.1-70B with vLLM and SentenceTransformer-based scoring.