Cost optimization guide
LLM cost optimization without wrecking quality
The best LLM cost optimization stack combines prompt compression, caching, model routing, and measurement.
The LLM cost optimization stack
- Prompt compression (highest impact) - Remove 60-85% of input tokens
- Caching - Avoid repeating identical API calls
- Model routing - Use cheaper models for simpler tasks
Frequently asked questions
Is compression better than switching models?
They solve different problems. Use both for maximum savings.
How quickly can I implement compression?
About 1 hour. Install, add 3 lines of code, and start compressing.
Build with less context
Put compression in front of your next LLM call.
Use the hosted API or run SuperCompress locally. Keep the evidence, drop the token waste, and measure the savings before it reaches your model.