Cloudflare has developed Infire, a new inference engine written in Rust, to efficiently handle AI tasks across its globally distributed network, addressing challenges associated with the use of centralized AI deployment models and the inefficiencies of running inference tasks on general-purpose engines like vLLM. Infire tackles these issues by maximizing GPU utilization and minimizing CPU overhead through advanced techniques such as continuous batching, paged KV caching, and optimized low-level operations for Nvidia hardware. This approach allows Cloudflare to run inference tasks faster and more resource-efficiently than before, reducing operational costs and freeing up CPU resources for other services. The development of Infire is part of Cloudflare's strategy to enhance its infrastructure for AI applications, with future plans to incorporate features like multi-GPU support and multi-tenancy. This advancement underscores Cloudflare's commitment to providing a robust platform for AI developers, improving the efficiency of requests served via its Workers AI platform.