vLLM
Run efficient language model inference with an OpenAI-compatible server
SGLang
Serve large language and multimodal models on your own infrastructure
About SGLang
SGLang is an open-source framework for serving large language and multimodal models. Developers can install it with Python packages or Docker, launch a model server, and connect applications through OpenAI-compatible endpoints. It supports model families such as Llama, Qwen, and DeepSeek, with deployment options ranging from a single accelerator to distributed clusters.
Its runtime combines prefix caching, optimized scheduling, speculative decoding, and parallel execution to improve inference throughput and latency. Support for different hardware platforms lets teams choose infrastructure that fits their workloads. SGLang is useful for engineers building production AI services who want direct control over model deployment and serving performance.
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- Website
- sglang.io
- Status
- Launched
- Category
- Developer tools
- Listed
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