vLLM vs SGLang
Compare vLLM and SGLang on deployment, pricing, model support, and more.
vLLM
- Tagline
- High-throughput LLM inference server with continuous batching and PagedAttention
- Description
- vLLM is an open-source, high-throughput inference engine for large language models. Its PagedAttention algorithm manages GPU memory efficiently, enabling 2–24× higher throughput than HuggingFace Transformers. It serves an OpenAI-compatible API, making it a drop-in replacement for production LLM serving.
- Category
- LLM Frameworks
- Pricing
- Free
- Metric
- 91,490 GitHub stars (source)
- Link
- Visit
SGLang
- Tagline
- Fast LLM serving framework — efficient serving for LLMs and vision-language models
- Description
- SGLang (Structured Generation Language) is an open-source framework for fast LLM serving and inference. It achieves 5–10× throughput improvements over naive inference through RadixAttention (efficient KV cache reuse), continuous batching, and structured generation with constrained decoding. Supports Llama, Mistral, Gemma, Qwen, and most open-source LLMs.
- Category
- LLM Frameworks
- Pricing
- Free
- Metric
- 35,806 GitHub stars (source)
- Link
- Visit
| Attribute | vLLM | SGLang |
|---|---|---|
| Tagline | High-throughput LLM inference server with continuous batching and PagedAttention | Fast LLM serving framework — efficient serving for LLMs and vision-language models |
| Category | LLM Frameworks | LLM Frameworks |
| Pricing | Free | Free |
| Description | vLLM is an open-source, high-throughput inference engine for large language models. Its PagedAttention algorithm manages GPU memory efficiently, enabling 2–24× higher throughput than HuggingFace Transformers. It serves an OpenAI-compatible API, making it a drop-in replacement for production LLM serving. | SGLang (Structured Generation Language) is an open-source framework for fast LLM serving and inference. It achieves 5–10× throughput improvements over naive inference through RadixAttention (efficient KV cache reuse), continuous batching, and structured generation with constrained decoding. Supports Llama, Mistral, Gemma, Qwen, and most open-source LLMs. |
| Metric | 91,490 GitHub stars (source) | 35,806 GitHub stars (source) |
| Link | Visit | Visit |