Lmsys · since Januar 2024 · 11× · last seen Jul 08, 2026
38
Momentum
SGLang is an Open Source serving framework for large language models (LLMs) and multimodal models, developed by researchers from UC Berkeley/Stanford and hosted by the nonprofit organization LMSYS. At its core is RadixAttention for efficient KV-Cache reuse, complemented by zero-overhead scheduling, continuous batching, speculative decoding (including the new DSpark method), and broad quantization support. The framework is deployed in production on over 400,000 GPUs worldwide and supports numerous models such as Llama, Qwen, DeepSeek, GLM, Gemma, and Mistral. SGLang offers an OpenAI-compatible API and runs on NVIDIA, AMD, Intel Xeon, Google TPU, and Ascend NPU hardware.
Momentum trend
19.05.17.08.
Features
| Throughput/Latency | DeepSeek-V4-Pro: 383.7 tok/s at B=1 on B300 with DSpark; up to ~20% higher throughput under high concurrency vs. fixed budget |
| License | Apache License 2.0 |
| Platform | NVIDIA, AMD, Intel Xeon, Google TPU, Ascend NPU; Linux, Docker, Kubernetes |
| Price | Free, open source (no license fees) |
| Protocol Compatibility | OpenAI-compatible API; compatible with Hugging Face APIs |
| Release Date | Initial release: January 17, 2024 |
| Supported Models/Providers | Llama, Qwen, DeepSeek, Kimi, GLM, GPT, Gemma, Mistral and more; also embedding, reward and diffusion models (WAN, Qwen-Image) |