Tag: vLLM
Transformer Efficiency Tricks: KV Caching and Continuous Batching in LLM Serving
Learn how KV caching and continuous batching optimize LLM serving. Explore memory trade-offs, vLLM implementation, and compression techniques like NVFP4 for faster inference.
Scaling Open-Source LLMs: Hardware, Serving Stacks, and Playbooks for 2026
Learn how to scale open-source LLMs in 2026 with the right hardware, serving stacks like vLLM, and a strategic playbook for enterprise deployment.
Batched Generation in LLM Serving: How Request Scheduling Shapes Output Speed and Quality
Batched generation in LLM serving boosts efficiency by processing multiple requests at once. How those requests are scheduled determines speed, fairness, and cost. Learn how continuous batching, PagedAttention, and smart scheduling impact output performance.
