LLM API Gateway Caching

Implement intelligent caching for your LLM API infrastructure. Reduce latency, cut costs, and improve response times with strategic response and prompt caching.

70% Cost Reduction
10x Faster Responses
99.9% Cache Hit Rate

Caching Strategies

Choose the right caching strategy for your LLM API

01

Response Caching

Cache complete API responses based on request hash. Eliminates redundant API calls for identical prompts.

02

Prompt Caching

Cache the prompt structure and reuse it across multiple requests. Particularly effective for long system prompts.

03

Semantic Caching

Use vector similarity to match semantically similar requests. Handles paraphrased prompts that mean the same thing.

04

TTL Caching

Set time-to-live for cached responses. Balance freshness with performance based on your use case.

05

Redis Integration

Use Redis for distributed caching across multiple servers. Ensures cache consistency in clustered environments.

06

Invalidation

Smart cache invalidation strategies. Clear outdated responses while maintaining high hit rates.

Cache Implementation

Understanding how LLM caching works

Cache Flow

When a request comes in, the gateway checks the cache before forwarding to the LLM provider.

Request
Cache Miss
LLM API
Request
Cache Hit
Return Cached

Best Practices

Follow these tips for optimal cache performance:

  • Use consistent request formatting for better hit rates
  • Implement cache key normalization (trim whitespace, lowercase)
  • Set appropriate TTL based on data freshness requirements
  • Monitor cache hit rates and adjust strategies accordingly
  • Use Redis Cluster for high availability
  • Implement cache warm-up for critical endpoints

Performance Impact

What proper caching can achieve for your API

70%
API Cost Savings
10x
Faster Responses
95%
Hit Rate Target
60%
Reduced Latency

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