Paid Guide · PDF · Infrastructure Economics
LLM Cost Optimization in Production:
From $500/month to $50
The infrastructure patterns that cut your API bill by 90% without degrading product quality.
One-time payment · PDF delivery after purchase
What this solves
Most AI apps waste money by default.
Most teams don’t have a model problem. They have a routing, caching, batching, and context-waste problem.
This guide breaks down the patterns that matter if you are already paying for traffic and want lower cost without turning the product into garbage.
Every chapter is implementation-focused and built around production constraints instead of benchmark theatre.
Inside the guide
5 cost-saving patterns.
01
Semantic Caching
Skip the model entirely on repeat or near-repeat requests using embedding similarity and Redis.
02
Prompt Compression
Reduce tokens before they hit the expensive model. Keep context, cut waste.
03
Model Routing
Cheap model for easy requests. Expensive model only when complexity actually requires it.
04
Batch Processing
Move non-realtime workloads off the hot path and compress infra cost with queues and batching.
05
Self-Hosted Inference
Know when Ollama or local GPUs are actually cheaper, and when they are just ops debt.
Bonus
30-day savings roadmap
A week-by-week sequence to cut waste without destabilizing the app.
Stop paying premium rates for avoidable mistakes.
If your traffic is real, infra discipline matters more than model brand loyalty.
Also from Supertute