From expensive tokens to intelligent compression: how we optimize LLM costs in production

498Advance runs multiple LLMs (Claude, Gemini, DeepSeek, OpenAI) in production and manages cost/reliability through three layers: automatic fallback policies, a router shadow that matches task complexity to the appropriate model tier, and local model deployment for routine tasks. The article also surveys compression techniques—quantization, pruning, and knowledge distillation—citing benchmarks like 2:4 Sparse Llama's 98.4% accuracy recovery and real-world cases from LinkedIn and Roblox.