Will the GKE Inference Gateway speed up every inference workload?

No. It helps only when requests share long, identical prompt prefixes, such as RAG over a fixed corpus or chat with a stable system persona. For one-shot prompts that differ every time, there is little or nothing to cache, so you pay the routing and index-maintenance overhead without the reuse benefit. Match it to your traffic shape first.

Why did Snap report a range of 75-80% rather than a single hit rate?

Because cache hit rate is not a fixed property of the gateway; it depends on how consistently your prompts share prefixes. Snap's "up to 75-80%" reflects a mature service mesh and disciplined prompt structure with llm-d and Envoy. Treat it as an achievable ceiling for a team that invests in prompt uniformity, not a default you get automatically.

What is the real operational cost of enabling prefix caching?

Two things. First, prompt drift quietly erodes your hit rate, so any change to system instructions or templates becomes a latency-affecting deploy. Second, the gateway polls cache and queue state across the cluster, which consumes control-plane resources during spikes, and an oversized prefix set can thrash and perform worse than round-robin. Both are manageable, but only if you monitor for them.

Should I trust the 92.8% faster time-to-first-token figure for my own cluster?

It is accurate for the tested shared-prefix workload, but TTFT is the metric most sensitive to cache hits, so it overstates the gain for mixed traffic. The 15.7% throughput improvement is the steadier number to plan capacity around. Benchmark your own representative prompt mix before promising any specific figure to stakeholders.

Is GKE cheaper than EKS for AI inference because of this gateway?

The control-plane prices sit in a similar band across providers, so that is not where savings come from. Real inference cost is dominated by GPU-hours, and the gateway's value is raising accelerator utilization by avoiding redundant recomputation. Validate Google's broader 30% cost-reduction claim against your own workload rather than assuming it, since it is a vendor figure, not a benchmark line item.

GKE Inference Gateway Prefix Caching: Don't Sign Up for the Cache Tax

Wed, 10 Jun 2026 00:00:00 +0000

A staff engineer I trust pinged me last quarter about prefix-cache-aware routing. He had read Google's benchmark cover to cover, had the throughput math exactly right, and had drawn the wrong conclusion from it: that flipping it on would hand his RAG assistant a permanent latency win. He shipped it. For two days the dashboards were beautiful. Then a Friday template tweak shaved his hit rate in half over the weekend and his pager went off Monday morning with nobody able to say why the latency had crept back to baseline. The headline was correct. The operating model behind it was not, and that gap is the whole story.

Recomputation on StorageNews

GKE Inference Gateway Prefix Caching: Don't Sign Up for the Cache Tax