GKE Inference Gateway Boosts AI Inference Efficiency
🚀 GKE Inference Gateway uses prefix caching and model-aware routing to reduce accelerator idle time and speed up LLM inference. By matching request prefixes to pods that already hold the KV cache, it avoids repeated recomputation and lowers latency compared with naive round-robin load balancing. Independent benchmarks show 15.7% higher throughput, 92.8% faster time-to-first-token, and 62.6% lower inter-token latency. Snap reports 75–80% prefix cache hit rates in production integrations.