Cloudflare details infrastructure engineering for hosting large language models on Workers AI, achieving 3x faster performance for Moonshot's Kimi K2.5. The post covers prefill-decode disaggregation for efficient GPU utilization, KV cache optimization with prompt caching for agent workloads, and integration with Moonshot's Mooncake framework for multi-GPU cache sharing.
Infrastructure
Building the foundation for running extra-large language models
Cloudflare demonstrates 3x performance gains for LLM inference by disaggregating prefill and decode compute stages and optimizing KV cache management with prompt caching, enabling efficient multi-GPU scaling on Workers AI.
Thursday, April 16, 2026 12:00 PM UTC2 MIN READSOURCE: Cloudflare BlogBY sys://pipeline
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infrastructure
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