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SGLang Release 26.06

This SGLang container release is intended for use on the NVIDIA® Hopper Architecture GPU, NVIDIA H100, the NVIDIA® Ampere Architecture GPU, NVIDIA A100, and the associated NVIDIA CUDA® 12 and NVIDIA cuDNN 9 libraries. The NVIDIA container image for the SGLang release is available on NGC.

Contents of the SGLang container

This container image contains the complete source of the version of SGLang in /opt/sglang. It is pre-built and installed in the Python default environment/usr/local/lib/python3.12/dist-packages/sglang/in the container image. Visit SGLang Docs to learn more about SGLang.

The NVIDIA SGLang Container is optimized for use with NVIDIA GPUs, and contains the following software for GPU acceleration.

  • Please see the CUDA section for the list of libraries inherited from CUDA container.
  • NVIDIA CUDA 13.3.0
  • SGLang 0.5.12.post1
  • flashinfer 0.6.12
  • transformers 5.6.0
  • flash-attention 2.7.4.post1
  • xgrammar 0.2.0
  • Torch 2.13.0a0+8145d630e8

Driver Requirements

Release 26.06 is based on CUDA 13.3.0. For comprehensive and up-to-date driver compatibility information, please refer to the following documentation:

Key Features and Enhancements

This SGLang release includes the following key features and enhancements.

  • Support for multi-node configurations.

  • GB300/B300 support.
  • RTX PRO™ 6000 Blackwell Server Edition support.

  • DGX Spark support.

  • Jetson Thor support.
  • Support for 8-bit floating point (FP8) precision on Hopper GPUs and above.

  • Support NVIDIA innovative 4-bit floating point NVFP4 format on Blackwell GPUs (including Jetson Thor and DGX Spark), which provides better training and inference performance with lower memory utilization.

  • Supported for DeepSeek-R1, Llama-3.1-8B-Instruct.
  • Support for openai/gpt-oss-20b and openai/gpt-oss-120b.
  • Support for Nemotron-3 Nano Omni
  • Qwen3.6-35B-A3B-FP8

Announcements

  • None.

Known Issues

  • MTP is not supported for NVIDIA-Nemotron-3-Super models.
  • There is a known issue with Phi 4 Multimodal Instruct FP8.
  • The 26.06 SGLang container release includes no known vulnerabilities (CVEs).
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