# EP223: Ollama vs vLLM vs SGLang

DevFeed: [EP223: Ollama vs vLLM vs SGLang](<https://devfeed.tech/articles/ep223-ollama-vs-vllm-vs-sglang-17985.md>)

Original publisher: [Read original article](<https://blog.bytebytego.com/p/ep223-ollama-vs-vllm-vs-sglang>)

Author: ByteByteGo

Published: 2026-08-22T15:31:34Z

Content type: comparison

Language: en

Sources: [ByteByteGo](<https://devfeed.tech/sources/bytebytego.md>)

Topics: [Ollama](<https://devfeed.tech/topics/ollama.md>), [sglang](<https://devfeed.tech/topics/sglang.md>), [vllm](<https://devfeed.tech/topics/vllm.md>), [Large Language Model](<https://devfeed.tech/topics/llm.md>), [API](<https://devfeed.tech/topics/api.md>), [Cache](<https://devfeed.tech/topics/cache.md>), [Agent Skills](<https://devfeed.tech/topics/agent-skills.md>)

Tags: [ai-agents](<https://devfeed.tech/tags/ai-agents.md>), [api](<https://devfeed.tech/tags/api.md>), [cache](<https://devfeed.tech/tags/cache.md>), [models](<https://devfeed.tech/tags/models.md>), [ollama](<https://devfeed.tech/tags/ollama.md>), [sglang](<https://devfeed.tech/tags/sglang.md>), [vllm](<https://devfeed.tech/tags/vllm.md>)

## AI overview

This comparison explains how Ollama, vLLM, and SGLang handle requests for open-weight models. Ollama uses a FIFO queue and pre-quantized GGUF models for local development and prototyping; vLLM uses continuous batching and PagedAttention for high-traffic serving; and SGLang uses prefix-aware scheduling and RadixAttention for agents, multi-turn chats, and structured outputs.

## Source excerpt

To use open-weight models on your machine, you have three main options: Ollama, vLLM, and SGLang. But each engine handles requests differently.