diff --git a/README.md b/README.md index e5cfd3d65..2beb407a4 100644 --- a/README.md +++ b/README.md @@ -22,28 +22,30 @@

## News +- [2026/07] 🔥 SGLang and Miles add day-0 support for Kimi K3 ([blog](https://lmsys.org/blog/2026-07-27-kimi-k3-day0-support/)). +- [2026/07] RadixArk and Google bring full SGLang features to TPUs ([blog](https://lmsys.org/blog/2026-07-30-sglang-google-tpu/)). +- [2026/07] Serving GLM5.2 NVFP4 agentic workloads with SGLang: Reaching 500 TPS in two weeks ([blog](https://lmsys.org/blog/2026-07-13-glm52-optimization/)). - [2026/06] 🔥 The next generation of speculative decoding: DFlash and Spec V2 ([blog](https://lmsys.org/blog/2026-06-15-next-generation-speculative-decoding-dflash-v2/)). -- [2026/04] 🔥 DeepSeek-V4 on Day 0: From Fast Inference to Verified RL with SGLang and Miles ([blog](https://lmsys.org/blog/2026-04-25-deepseek-v4/)). - [2026/06] SGLang provides day-0 support for latest open models ([Nemotron 3 Ultra](https://lmsys.org/blog/2026-06-04-nvidia-run-nemotron-3-ultra/), [Nemotron 3 Super](https://lmsys.org/blog/2026-03-11-run-nvidia-nemotron-3-super/), [Higgs Audio v3 TTS](https://lmsys.org/blog/2026-06-04-higgs-audio-v3-tts/)). +- [2026/04] 🔥 DeepSeek-V4 on Day 0: From Fast Inference to Verified RL with SGLang and Miles ([blog](https://lmsys.org/blog/2026-04-25-deepseek-v4/)). - [2026/02] 🔥 Unlocking 25x Inference Performance with SGLang on NVIDIA GB300 NVL72 ([blog](https://lmsys.org/blog/2026-02-20-gb300-inferencex/)). - [2026/01] SGLang Diffusion accelerates video and image generation ([blog](https://lmsys.org/blog/2026-01-16-sglang-diffusion/)). -- [2025/12] SGLang provides day-0 support for latest open models ([MiMo-V2-Flash](https://lmsys.org/blog/2025-12-16-mimo-v2-flash/), [Nemotron 3 Nano](https://lmsys.org/blog/2025-12-15-run-nvidia-nemotron-3-nano/), [Mistral Large 3](https://github.com/sgl-project/sglang/pull/14213), [LLaDA 2.0 Diffusion LLM](https://lmsys.org/blog/2025-12-19-diffusion-llm/), [MiniMax M2](https://lmsys.org/blog/2025-11-04-miminmax-m2/)). -- [2025/10] SGLang now runs natively on TPU with the SGLang-Jax backend ([blog](https://lmsys.org/blog/2025-10-29-sglang-jax/)).
More +- [2025/12] SGLang provides day-0 support for latest open models ([MiMo-V2-Flash](https://lmsys.org/blog/2025-12-16-mimo-v2-flash/), [Nemotron 3 Nano](https://lmsys.org/blog/2025-12-15-run-nvidia-nemotron-3-nano/), [Mistral Large 3](https://github.com/sgl-project/sglang/pull/14213), [LLaDA 2.0 Diffusion LLM](https://lmsys.org/blog/2025-12-19-diffusion-llm/), [MiniMax M2](https://lmsys.org/blog/2025-11-04-miminmax-m2/)). +- [2025/11] SGLang Diffusion accelerates video and image generation ([blog](https://lmsys.org/blog/2025-11-07-sglang-diffusion/)). +- [2025/10] SGLang now runs natively on TPU with the SGLang-Jax backend ([blog](https://lmsys.org/blog/2025-10-29-sglang-jax/)). +- [2025/10] PyTorch Conference 2025 SGLang Talk ([slide](https://github.com/sgl-project/sgl-learning-materials/blob/main/slides/sglang_pytorch_2025.pdf)). +- [2025/10] SGLang x Nvidia SF Meetup on 10/2 ([recap](https://x.com/lmsysorg/status/1975339501934510231)). - [2025/09] Deploying DeepSeek on GB200 NVL72 with PD and Large Scale EP (Part II): 3.8x Prefill, 4.8x Decode Throughput ([blog](https://lmsys.org/blog/2025-09-25-gb200-part-2/)). - [2025/09] SGLang Day 0 Support for DeepSeek-V3.2 with Sparse Attention ([blog](https://lmsys.org/blog/2025-09-29-deepseek-V32/)). - [2025/08] SGLang x AMD SF Meetup on 8/22: Hands-on GPU workshop, tech talks by AMD/xAI/SGLang, and networking ([Roadmap](https://github.com/sgl-project/sgl-learning-materials/blob/main/slides/amd_meetup_sglang_roadmap.pdf), [Large-scale EP](https://github.com/sgl-project/sgl-learning-materials/blob/main/slides/amd_meetup_sglang_ep.pdf), [Highlights](https://github.com/sgl-project/sgl-learning-materials/blob/main/slides/amd_meetup_highlights.pdf), [AITER/MoRI](https://github.com/sgl-project/sgl-learning-materials/blob/main/slides/amd_meetup_aiter_mori.pdf), [Wave](https://github.com/sgl-project/sgl-learning-materials/blob/main/slides/amd_meetup_wave.pdf)). - -- [2025/11] SGLang Diffusion accelerates video and image generation ([blog](https://lmsys.org/blog/2025-11-07-sglang-diffusion/)). -- [2025/10] PyTorch Conference 2025 SGLang Talk ([slide](https://github.com/sgl-project/sgl-learning-materials/blob/main/slides/sglang_pytorch_2025.pdf)). -- [2025/10] SGLang x Nvidia SF Meetup on 10/2 ([recap](https://x.com/lmsysorg/status/1975339501934510231)). - [2025/08] SGLang provides day-0 support for OpenAI gpt-oss model ([instructions](https://github.com/sgl-project/sglang/issues/8833)) - [2025/06] SGLang, the high-performance serving infrastructure powering trillions of tokens daily, has been awarded the third batch of the Open Source AI Grant by a16z ([a16z blog](https://a16z.com/advancing-open-source-ai-through-benchmarks-and-bold-experimentation/)). -- [2025/05] Deploying DeepSeek with PD Disaggregation and Large-scale Expert Parallelism on 96 H100 GPUs ([blog](https://lmsys.org/blog/2025-05-05-large-scale-ep/)). - [2025/06] Deploying DeepSeek on GB200 NVL72 with PD and Large Scale EP (Part I): 2.7x Higher Decoding Throughput ([blog](https://lmsys.org/blog/2025-06-16-gb200-part-1/)). +- [2025/05] Deploying DeepSeek with PD Disaggregation and Large-scale Expert Parallelism on 96 H100 GPUs ([blog](https://lmsys.org/blog/2025-05-05-large-scale-ep/)). - [2025/03] Supercharge DeepSeek-R1 Inference on AMD Instinct MI300X ([AMD blog](https://rocm.blogs.amd.com/artificial-intelligence/DeepSeekR1-Part2/README.html)) - [2025/03] SGLang Joins PyTorch Ecosystem: Efficient LLM Serving Engine ([PyTorch blog](https://pytorch.org/blog/sglang-joins-pytorch/)) - [2025/02] Unlock DeepSeek-R1 Inference Performance on AMD Instinctâ„¢ MI300X GPU ([AMD blog](https://rocm.blogs.amd.com/artificial-intelligence/DeepSeekR1_Perf/README.html)) @@ -80,7 +82,7 @@ Its core features include: Learn more in the release blogs: [v0.2 blog](https://lmsys.org/blog/2024-07-25-sglang-llama3/), [v0.3 blog](https://lmsys.org/blog/2024-09-04-sglang-v0-3/), [v0.4 blog](https://lmsys.org/blog/2024-12-04-sglang-v0-4/), [Large-scale expert parallelism](https://lmsys.org/blog/2025-05-05-large-scale-ep/), [GB200 rack-scale parallelism](https://lmsys.org/blog/2025-09-25-gb200-part-2/), [GB300 long context](https://lmsys.org/blog/2026-02-19-gb300-longctx/). ## Adoption and Sponsorship -SGLang has been deployed at large scale, generating trillions of tokens in production each day. It is trusted and adopted by a wide range of leading enterprises and institutions, including xAI, AMD, NVIDIA, Intel, LinkedIn, Cursor, Oracle Cloud, Google Cloud, Microsoft Azure, AWS, Atlas Cloud, Voltage Park, Nebius, DataCrunch, Novita, InnoMatrix, Modal, MIT, UCLA, the University of Washington, Stanford, UC Berkeley, Tsinghua University, Jam & Tea Studios, Baseten, and other major technology organizations. +SGLang has been deployed at large scale, generating trillions of tokens in production each day. It is trusted and adopted by a wide range of leading enterprises and institutions, including xAI, NVIDIA, AMD, Intel, LinkedIn, Cursor, Oracle Cloud, Google Cloud, Microsoft Azure, AWS, Atlas Cloud, Voltage Park, Nebius, DataCrunch, Novita, RunPod, InnoMatrix, Modal, MIT, UCLA, the University of Washington, Stanford, UC Berkeley, Tsinghua University, Baseten, Baidu, AntGroup, Alibaba, Tencent, and other major technology organizations. As an open-source LLM inference engine, SGLang has become the de facto industry standard, with deployments running on over 400,000 GPUs worldwide. SGLang is currently hosted under the non-profit open-source organization [LMSYS](https://lmsys.org/about/).