SGLang

Health v2 · maintenance only

Adoption not part of the score

32504 stars · 8238 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

SGLang is a high-performance open-source serving framework for large language models and multimodal models, offering low-latency, high-throughput inference from a single GPU to distributed clusters. It provides OpenAI-compatible APIs, RadixAttention prefix caching, speculative decoding, and broad hardware support including NVIDIA, AMD, TPU, and Ascend accelerators.

Use cases

• serve an llm with an openai-compatible api
• deploy a self-hosted inference server for llama or qwen
• run high-throughput batch inference on gpus
• serve vision-language models
• speed up chatbot serving with prefix caching
• run rl training rollouts with fast inference
• serve deepseek or glm models on multi-gpu clusters

When to choose

• you need production-grade, low-latency LLM serving with high throughput
• you want OpenAI-compatible endpoints for self-hosted open models
• you need multi-GPU or multi-node tensor parallelism and disaggregated prefill/decode
• you serve agentic or RAG workloads with heavy shared prefixes
• you need day-0 support for the latest open models

When to avoid

• you only need to run inference locally on a laptop without GPUs
• you want a simple single-file inference script rather than a server
• your models are unsupported architectures outside its supported list
• you need a managed cloud service rather than self-hosted infrastructure

Facets

framework · maturity stable

llm-inference http-server api-framework machine-learning gpu-computing rag large-language-models machine-learning deep-learning gpu-computing apis self-hosted python cloud self-hosted serving inference-engine openai-compatible-api radixattention prefix-caching speculative-decoding multimodal vllm-alternative tensor-parallelism diffusion-models linux docker gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="sgl-project/sglang")