vLLM vs SGLang: Which Inference Engine for Agents (2026)
vLLM vs SGLang compared for agent workloads in 2026: throughput, latency, prefix reuse, and which inference engine to run for which use case.
Tag: #inference-engine
AI Agent Infrastructure Stack 2026
A map of the 2026 AI agent infrastructure stack: inference engines, model gateways, agent frameworks, and dev environments, with the right tool for each layer.
SGLang Explained: The Low-Latency Inference Engine for Agents
How SGLang works, why RadixAttention gives agents faster prefix reuse, and when to choose it over vLLM for production inference in 2026.
vLLM Explained: The Inference Engine Behind Agent Stacks
How vLLM works under the hood, why PagedAttention matters for agent workloads, and where it fits in a production agent infrastructure stack in 2026.