Cost Optimization
Explicit Cache: Practical Comparison
One line of code — guaranteed hits. In production, you must use explicit caching: implicit caching is unreliable in distributed architectures.
Why Implicit Caching Is Unreliable
⚠️ Why is implicit caching unreliable in production?
Your Request
→
Load Balancer
→
Randomly routed to one of these nodes:
Node A
cached
cached
Node B
no cache
no cache
Node C
no cache
no cache
Cloud LLMs run on multiple GPU nodes and every request is randomly routed. Node A has your cache; B and C don't. Whether you get a hit is pure luck — actual hit rate <30%.
✅ Explicit Cache: Mark Your Anchor Point
Add one line of cache_control in the API request and the platform guarantees routing to a node that has the cache. No random routing dependency — hit rate approaches 100%.
Implicit Cache (automatic)
No code changes needed
Hit not guaranteed
Discount: 20% of standard price
High MISS rate in distributed environments
Explicit Cache (recommended)
Add one line of cache_control
Platform guarantees routed hit
Discount: 10% of standard price
Save 90% on input costs
Code Examples for Three Platforms
Hit Rate Simulation Comparison
Simulate 10 Requests: Implicit vs. Explicit Cache Hit Comparison
Implicit Cache (random routing)
Explicit Cache (guaranteed routing)
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Implicit Hit Count
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Explicit Hit Count
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Cost Saved (Explicit)
Engineering Conclusion: Explicit caching is a must in production. Relying on random routing to save money is like counting on luck — both unreliable and unprofessional.