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SGLang Info

Overview of SGLang, CI infrastructure, and Docker images

Stable Docker Image

Official SGLang release images for production use.

lmsysorg/sglang Docker Hub
docker pull lmsysorg/sglang:latest
ROCm Nightly Image

AMD ROCm nightly builds for MI300X/MI325X/MI355X development.

rocm/sgl-dev Docker Hub
docker pull rocm/sgl-dev:latest
What is SGLang?

SGLang is a fast serving framework for large language models and vision-language models. It makes your model fast and easy to use with a flexible frontend language and powerful backend runtime.

For an in-depth introduction with setup instructions and examples on AMD Instinct GPUs, see the ROCm blog post: SGLang on AMD Instinct GPUs.

Key Capabilities
  • High-throughput LLM/VLM inference serving
  • Supports 100+ model architectures: dense LLMs, MoE, VLMs, diffusion models
  • Multi-GPU: tensor parallelism (TP), expert parallelism (EP), data parallelism (DP)
  • FP8/INT4 quantization, continuous batching, RadixAttention (prefix caching)
  • Multi-platform: NVIDIA, AMD (MI300X/MI325X/MI355X), Ascend NPU
  • Community cookbook: cookbook.sglang.io
What is SGLang CI?

SGLang's upstream CI (sgl-project/sglang) runs automated tests on every PR and nightly to validate correctness and performance across GPU platforms.

AMD CI Infrastructure
Self-hosted runners linux-mi325-gpu-8 (MI300X/MI325X)
linux-mi35x-gpu-8 (MI355X)
ROCm versions ROCm 7.0 (default) and ROCm 7.2
Execution Docker-based: each job spins up a ROCm container, installs dependencies, runs tests
Test registration Tests live in test/registered/amd/ and register via register_amd_ci()
What is Nightly CI?

Nightly CI runs every night (not on every PR) to test things that are too expensive or slow for per-PR testing:

TypeWhat it testsExample
Accuracy Run models end-to-end, check output quality against benchmarks MiniMax-M2.5, DeepSeek-V3.2, GLM-5
Performance Measure throughput/latency, detect regressions DeepSeek-V3.2 MTP decode speed
Large models 8-GPU models too big for per-PR runners Kimi-K2.5 (TP=8), Qwen3-235B
Workflow files: nightly-test-amd.yml (ROCm 7.0) & nightly-test-amd-rocm720.yml (ROCm 7.2). Each model gets up to 4 nightly jobs (MI30x + MI35x, each on ROCm 7.0 + 7.2).
SGLang Cookbook

The SGLang Cookbook is a community-maintained site with practical guides for deploying SGLang with various models on different hardware. Includes AMD-specific deployment guides.