From a01a8e1ed962168671243e4fcd52cc199c20fe12 Mon Sep 17 00:00:00 2001 From: Douglas Yang Date: Fri, 17 Jul 2026 16:33:19 -0700 Subject: [PATCH] docs(cookbook): replace pinned nightly/dev images with :latest (#31610) Co-authored-by: Claude Opus 4.8 (1M context) --- .../cookbook/autoregressive/Google/Gemma4.mdx | 12 +++--------- .../autoregressive/InclusionAI/Ling-2.5-1T.mdx | 9 +++------ .../autoregressive/InclusionAI/Ring-2.5-1T.mdx | 9 +++------ .../autoregressive/MiniMax/MiniMax-M3.mdx | 7 +++---- .../NVIDIA/Nemotron3-Nano-Omni.mdx | 2 +- .../autoregressive/Poolside/Laguna-M.1.mdx | 6 +++--- .../autoregressive/Poolside/Laguna-XS-2.1.mdx | 2 +- .../autoregressive/Poolside/Laguna-XS.2.mdx | 5 ++--- .../cookbook/autoregressive/Qwen/Qwen3.6.mdx | 5 +---- .../autoregressive/StepFun/Step3.5.mdx | 4 ++-- .../Tencent/Hunyuan3-Preview.mdx | 10 +++------- .../autoregressive/Xiaomi/MiMo-V2-Flash.mdx | 4 ++-- .../snippets/configs/MiniMaxAI/minimax-m3.jsx | 17 ++++++++--------- .../snippets/configs/poolside/laguna-m1.jsx | 18 ++++++++---------- .../snippets/configs/poolside/laguna-xs21.jsx | 8 ++++---- 15 files changed, 47 insertions(+), 71 deletions(-) diff --git a/docs_new/cookbook/autoregressive/Google/Gemma4.mdx b/docs_new/cookbook/autoregressive/Google/Gemma4.mdx index 78e1218dd..f383329bf 100644 --- a/docs_new/cookbook/autoregressive/Google/Gemma4.mdx +++ b/docs_new/cookbook/autoregressive/Google/Gemma4.mdx @@ -77,21 +77,15 @@ pip install 'git+https://github.com/sgl-project/sglang.git#subdirectory=python' pip install 'git+https://github.com/huggingface/transformers.git@1423d22f7a3b62e8c70ad67b58ec25cd9b675897' ``` -### Docker (prebuilt dev image) +### Docker -Prebuilt development images bundle SGLang together with the matching transformers commit preinstalled, so no manual install is needed. All tags are multi-arch (`amd64` + `arm64`): - -| Tag | CUDA | Hardware | -| --- | --- | --- | -| `lmsysorg/sglang:dev-gemma-4-12B` | 13.0 | Default — amd64 (H200 / B200) + arm64 (GB200 / GB300) | -| `lmsysorg/sglang:dev-cu13-gemma-4-12B` | 13.0 | Alias of the default tag | -| `lmsysorg/sglang:dev-cu12-gemma-4-12B` | 12.9 | CUDA 12.x hosts | +`lmsysorg/sglang:latest` (CUDA 13.0, multi-arch `amd64` + `arm64`) runs on both Hopper (H200) and Blackwell (B200 / GB200 / GB300): ```bash Command docker run --gpus all --ipc=host --shm-size 32g \ -v ~/.cache/huggingface:/root/.cache/huggingface \ -p 30000:30000 \ - lmsysorg/sglang:dev-gemma-4-12B \ + lmsysorg/sglang:latest \ sglang serve --model-path google/gemma-4-12B-it \ --reasoning-parser gemma4 --tool-call-parser gemma4 \ --host 0.0.0.0 --port 30000 diff --git a/docs_new/cookbook/autoregressive/InclusionAI/Ling-2.5-1T.mdx b/docs_new/cookbook/autoregressive/InclusionAI/Ling-2.5-1T.mdx index 68ab2a43c..008c2dd0c 100644 --- a/docs_new/cookbook/autoregressive/InclusionAI/Ling-2.5-1T.mdx +++ b/docs_new/cookbook/autoregressive/InclusionAI/Ling-2.5-1T.mdx @@ -24,14 +24,11 @@ metatags: ## 2. SGLang Installation -Ling-2.5-1T requires a specific SGLang Docker image: +Ling-2.5-1T runs on the standard SGLang Docker image: ```bash Command -# For H200/B200 -docker pull lmsysorg/sglang:nightly-dev-20260213-a0ebaa64 - -# For GB200/GB300 -docker pull lmsysorg/sglang:nightly-dev-cu13-20260213-a0ebaa64 +# NVIDIA (H200 / B200 / GB200 / GB300) +docker pull lmsysorg/sglang:latest ``` For other installation methods, please refer to the [official SGLang installation guide](../../../docs/get-started/install). diff --git a/docs_new/cookbook/autoregressive/InclusionAI/Ring-2.5-1T.mdx b/docs_new/cookbook/autoregressive/InclusionAI/Ring-2.5-1T.mdx index ad711e7ee..42fb93cd6 100644 --- a/docs_new/cookbook/autoregressive/InclusionAI/Ring-2.5-1T.mdx +++ b/docs_new/cookbook/autoregressive/InclusionAI/Ring-2.5-1T.mdx @@ -25,14 +25,11 @@ metatags: ## 2. SGLang Installation -Ring-2.5-1T requires a specific SGLang Docker image: +Ring-2.5-1T runs on the standard SGLang Docker image: ```bash Command -# For H200/B200 -docker pull lmsysorg/sglang:nightly-dev-20260213-a0ebaa64 - -# For GB200/GB300 -docker pull lmsysorg/sglang:nightly-dev-cu13-20260213-a0ebaa64 +# NVIDIA (H200 / B200 / GB200 / GB300) +docker pull lmsysorg/sglang:latest # For MI300X/325X docker pull lmsysorg/sglang:v0.5.9-rocm700-mi30x diff --git a/docs_new/cookbook/autoregressive/MiniMax/MiniMax-M3.mdx b/docs_new/cookbook/autoregressive/MiniMax/MiniMax-M3.mdx index bc081ee38..19723cad6 100644 --- a/docs_new/cookbook/autoregressive/MiniMax/MiniMax-M3.mdx +++ b/docs_new/cookbook/autoregressive/MiniMax/MiniMax-M3.mdx @@ -35,11 +35,10 @@ Then run the **Python** output of the command panel below in that environment. T ```bash Command -# Pull the M3 image the command panel selects for your platform, e.g.: -docker pull lmsysorg/sglang:dev-cu13-minimax-m3 +docker pull lmsysorg/sglang:latest ``` -The command panel below fills in the right tag per platform: `dev-cu13-minimax-m3` (CUDA 13 — B300, GB200, GB300), `dev-cu12-minimax-m3` (CUDA 12 — Hopper H200), or `dev-minimax-m3` (default). On AMD Instinct it uses the matching ROCm image (MI300X/MI325X → `aigmkt/minimax-m3-sglang-rocm700-mi30x`, MI350X/MI355X → `aigmkt/minimax-m3-sglang-rocm720-mi35x`). For how to launch the image, see [Install → Method 3: Using Docker](../../../docs/get-started/install#method-3-using-docker), substituting the inner `sglang serve ...` with what the command generator produces. +On NVIDIA the command panel below uses `lmsysorg/sglang:latest` (CUDA 13, multi-arch — H200 + all Blackwell). On AMD Instinct it uses the matching ROCm image (MI300X/MI325X → `aigmkt/minimax-m3-sglang-rocm700-mi30x`, MI350X/MI355X → `aigmkt/minimax-m3-sglang-rocm720-mi35x`). For how to launch the image, see [Install → Method 3: Using Docker](../../../docs/get-started/install#method-3-using-docker), substituting the inner `sglang serve ...` with what the command generator produces. These M3 dev images now **bundle MiniMax's MSA sparse-attention kernel** (`fmha_sm100`), so Blackwell users get the recommended fast path automatically — no manual install needed (see **§2.1**). On a custom image without it, the same recipe still serves on the built-in Triton sparse path. @@ -87,7 +86,7 @@ Key characteristics as served by SGLang: ### 2.1 MSA sparse-attention fast path (recommended for Blackwell users) -[MiniMax MSA](https://github.com/MiniMax-AI/MSA) (`fmha_sm100`, MIT-licensed) is the recommended Blackwell kernel for M3's main sparse-attention step — faster and more memory-efficient than the built-in Triton fallback. **It ships pre-installed in the M3 dev image** (`lmsysorg/sglang:dev-minimax-m3`, also published under the `dev-cu13-minimax-m3` tag), so the Blackwell recipe above engages it automatically with no extra setup — `import fmha_sm100` works out of the box and the kernels JIT-compile on first use. It is otherwise purely additive: on a custom image, install it (below) and the recipe engages it automatically; without it the same recipe still serves on the built-in Triton path. The swap is numerically equivalent (cosine ≥ 0.99999 vs Triton), decode stays CUDA-graph-capturable, prefill TTFT drops ~9–12% at 8K–64K context, and the MSA path survives memory configurations where the Triton path OOMs. +[MiniMax MSA](https://github.com/MiniMax-AI/MSA) (`fmha_sm100`, MIT-licensed) is the recommended Blackwell kernel for M3's main sparse-attention step — faster and more memory-efficient than the built-in Triton fallback. **It ships pre-installed in `lmsysorg/sglang:latest`**, so the Blackwell recipe above engages it automatically with no extra setup — `import fmha_sm100` works out of the box and the kernels JIT-compile on first use. It is otherwise purely additive: on a custom image, install it (below) and the recipe engages it automatically; without it the same recipe still serves on the built-in Triton path. The swap is numerically equivalent (cosine ≥ 0.99999 vs Triton), decode stays CUDA-graph-capturable, prefill TTFT drops ~9–12% at 8K–64K context, and the MSA path survives memory configurations where the Triton path OOMs. **Requirements** (from the [MSA README](https://github.com/MiniMax-AI/MSA#requirements)): diff --git a/docs_new/cookbook/autoregressive/NVIDIA/Nemotron3-Nano-Omni.mdx b/docs_new/cookbook/autoregressive/NVIDIA/Nemotron3-Nano-Omni.mdx index fce05d5cf..29bd16733 100644 --- a/docs_new/cookbook/autoregressive/NVIDIA/Nemotron3-Nano-Omni.mdx +++ b/docs_new/cookbook/autoregressive/NVIDIA/Nemotron3-Nano-Omni.mdx @@ -49,7 +49,7 @@ pip install sglang uv pip install 'git+https://github.com/sgl-project/sglang.git#subdirectory=python' # Or use Docker -docker pull lmsysorg/sglang:dev-cu13-nemotronh-nano-omni-reasoning-v3 +docker pull lmsysorg/sglang:latest ``` For the full Docker setup and other installation methods, refer to the [official SGLang installation guide](../../../docs/get-started/install). diff --git a/docs_new/cookbook/autoregressive/Poolside/Laguna-M.1.mdx b/docs_new/cookbook/autoregressive/Poolside/Laguna-M.1.mdx index 2e65f387b..ea643df4a 100644 --- a/docs_new/cookbook/autoregressive/Poolside/Laguna-M.1.mdx +++ b/docs_new/cookbook/autoregressive/Poolside/Laguna-M.1.mdx @@ -27,15 +27,15 @@ cd sglang uv pip install -e python ``` -Then run the **Python** output of the command panel below in that environment. The **Docker** tab is simpler — its image (`dev-cu13-618-nightly`) bundles the CUDA-13 runtime and the M.1 code. Once M.1 support lands in a tagged release, `uv pip install sglang` will pull it directly. +Then run the **Python** output of the command panel below in that environment. The **Docker** tab is simpler — `lmsysorg/sglang:latest` bundles the CUDA-13 runtime and the M.1 code. ```bash Command -# Pinned nightly with the Laguna-M.1 build (PR #28400 + #28604; CUDA 13 — covers H200 + all Blackwell): -docker pull lmsysorg/sglang:dev-cu13-618-nightly +# CUDA 13 — covers H200 + all Blackwell: +docker pull lmsysorg/sglang:latest ``` For how to launch the image, see [Install → Method 3: Using Docker](../../../docs/get-started/install#method-3-using-docker). Substitute the inner `sglang serve ...` with what the command generator below produces. diff --git a/docs_new/cookbook/autoregressive/Poolside/Laguna-XS-2.1.mdx b/docs_new/cookbook/autoregressive/Poolside/Laguna-XS-2.1.mdx index 39e6cf1b1..5423eeda2 100644 --- a/docs_new/cookbook/autoregressive/Poolside/Laguna-XS-2.1.mdx +++ b/docs_new/cookbook/autoregressive/Poolside/Laguna-XS-2.1.mdx @@ -34,7 +34,7 @@ Then run the **Python** output of the command panel below in that environment. ```bash Command -docker pull lmsysorg/sglang:dev-cu13-laguna-xs-2-1 +docker pull lmsysorg/sglang:latest ``` For how to launch the image, see [Install → Method 3: Using Docker](../../../docs/get-started/install#method-3-using-docker). Substitute the inner `sglang serve ...` with what the command generator below produces. diff --git a/docs_new/cookbook/autoregressive/Poolside/Laguna-XS.2.mdx b/docs_new/cookbook/autoregressive/Poolside/Laguna-XS.2.mdx index b8aef70b1..eeddd0d7c 100644 --- a/docs_new/cookbook/autoregressive/Poolside/Laguna-XS.2.mdx +++ b/docs_new/cookbook/autoregressive/Poolside/Laguna-XS.2.mdx @@ -62,9 +62,8 @@ python3 -m pip install --extra-index-url https://docs.sglang.ai/whl/cu130 \ python3 -m pip install --extra-index-url https://docs.sglang.ai/whl/cu129 \ "sglang[all]==0.5.12.dev20260509+g096ad02b0" -# Or use Docker (multi-arch amd64/arm64) -docker pull lmsysorg/sglang:dev-cu13-laguna-xs2 # CUDA 13 (H200 / B200) -docker pull lmsysorg/sglang:dev-cu12-laguna-xs2 # CUDA 12 (H200) +# Or use Docker (multi-arch amd64/arm64; CUDA 13, H200 / B200) +docker pull lmsysorg/sglang:latest ``` For the full Docker setup and other installation methods, please refer to the [official SGLang installation guide](../../../docs/get-started/install). diff --git a/docs_new/cookbook/autoregressive/Qwen/Qwen3.6.mdx b/docs_new/cookbook/autoregressive/Qwen/Qwen3.6.mdx index 58ffa02be..92063dd59 100644 --- a/docs_new/cookbook/autoregressive/Qwen/Qwen3.6.mdx +++ b/docs_new/cookbook/autoregressive/Qwen/Qwen3.6.mdx @@ -78,11 +78,8 @@ uv pip install sglang # Or install from source uv pip install 'git+https://github.com/sgl-project/sglang.git#subdirectory=python' -# Or use Docker (NVIDIA GPUs) +# Or use Docker (NVIDIA GPUs; also serves the NVFP4 variant nvidia/Qwen3.6-27B-NVFP4) docker pull lmsysorg/sglang:latest - -# For the NVFP4 variant (nvidia/Qwen3.6-27B-NVFP4), use the dedicated dev image -docker pull lmsysorg/sglang:dev-cu13-dev-qwen36-27b-nvfp4 ``` For the full Docker setup and other installation methods, please refer to the [official SGLang installation guide](../../../docs/get-started/install). diff --git a/docs_new/cookbook/autoregressive/StepFun/Step3.5.mdx b/docs_new/cookbook/autoregressive/StepFun/Step3.5.mdx index 82c8a1d5a..1ff5a82b6 100644 --- a/docs_new/cookbook/autoregressive/StepFun/Step3.5.mdx +++ b/docs_new/cookbook/autoregressive/StepFun/Step3.5.mdx @@ -22,14 +22,14 @@ Step-3.5-Flash is currently available in SGLang via Docker image install. ### Docker (NVIDIA) ```bash Command # Pull the docker image -docker pull lmsysorg/sglang:dev-pr-18084 +docker pull lmsysorg/sglang:latest # Launch the container docker run -it --gpus all \ --shm-size=32g \ --ipc=host \ --network=host \ - lmsysorg/sglang:dev-pr-18084 bash + lmsysorg/sglang:latest bash ``` ### Docker (AMD ROCm) diff --git a/docs_new/cookbook/autoregressive/Tencent/Hunyuan3-Preview.mdx b/docs_new/cookbook/autoregressive/Tencent/Hunyuan3-Preview.mdx index 982a4e043..e84d756f4 100644 --- a/docs_new/cookbook/autoregressive/Tencent/Hunyuan3-Preview.mdx +++ b/docs_new/cookbook/autoregressive/Tencent/Hunyuan3-Preview.mdx @@ -65,17 +65,13 @@ Please refer to the [official SGLang installation guide](../../../docs/get-start - NVIDIA H200 / B200 - `lmsysorg/sglang:hy3-preview` - - - NVIDIA B300 / GB300 - `lmsysorg/sglang:hy3-preview-cu130` + NVIDIA H200 / B200 / B300 / GB300 + `lmsysorg/sglang:latest` -The `hy3-preview` tag bundles the HYV3 model code, the `hunyuan` tool-call / reasoning parsers, and the MTP draft-module runtime. +`lmsysorg/sglang:latest` bundles the HYV3 model code, the `hunyuan` tool-call / reasoning parsers, and the MTP draft-module runtime. For SGLang CPU installation, please refer to the [CPU version installation guide](../../../docs/hardware-platforms/cpu_server#installation). diff --git a/docs_new/cookbook/autoregressive/Xiaomi/MiMo-V2-Flash.mdx b/docs_new/cookbook/autoregressive/Xiaomi/MiMo-V2-Flash.mdx index ecd602190..fb6971bb5 100644 --- a/docs_new/cookbook/autoregressive/Xiaomi/MiMo-V2-Flash.mdx +++ b/docs_new/cookbook/autoregressive/Xiaomi/MiMo-V2-Flash.mdx @@ -23,14 +23,14 @@ MiMo-V2-Flash is currently available in SGLang via Docker image and pip install. ```bash Command # Pull the docker image -docker pull lmsysorg/sglang:dev-pr-15207 +docker pull lmsysorg/sglang:latest # Launch the container docker run -it --gpus all \ --shm-size=32g \ --ipc=host \ --network=host \ - lmsysorg/sglang:dev-pr-15207 bash + lmsysorg/sglang:latest bash ``` ### Pip Installation diff --git a/docs_new/src/snippets/configs/MiniMaxAI/minimax-m3.jsx b/docs_new/src/snippets/configs/MiniMaxAI/minimax-m3.jsx index 7263934db..2a0c47b62 100644 --- a/docs_new/src/snippets/configs/MiniMaxAI/minimax-m3.jsx +++ b/docs_new/src/snippets/configs/MiniMaxAI/minimax-m3.jsx @@ -92,14 +92,13 @@ sgl-eval run mmmu_pro \\ ], dockerImages: { - // M3-specific dev images (multi-arch amd64+arm64). cu13 carries the sm_103 - // (B300/GB300) + Grace arm64 builds; cu12 is the Hopper/CUDA-12 build; - // dev-minimax-m3 is the rolling default. - b200: "lmsysorg/sglang:dev-minimax-m3", - b300: "lmsysorg/sglang:dev-cu13-minimax-m3", - gb200: "lmsysorg/sglang:dev-cu13-minimax-m3", - gb300: "lmsysorg/sglang:dev-cu13-minimax-m3", - h200: "lmsysorg/sglang:dev-cu12-minimax-m3", + // lmsysorg/sglang:latest (cu13, multi-arch amd64+arm64) covers H200 + all + // Blackwell (incl. sm_103 B300/GB300 and Grace arm64). + b200: "lmsysorg/sglang:latest", + b300: "lmsysorg/sglang:latest", + gb200: "lmsysorg/sglang:latest", + gb300: "lmsysorg/sglang:latest", + h200: "lmsysorg/sglang:latest", // AMD ROCm images — published M3 builds, by arch (gfx942 -> mi30x, gfx950 -> mi35x). mi300x: "aigmkt/minimax-m3-sglang-rocm700-mi30x", mi325x: "aigmkt/minimax-m3-sglang-rocm700-mi30x", @@ -199,7 +198,7 @@ sgl-eval run mmmu_pro \\ // B300 / GB200 / GB300, tp8 on B200. fa4 + page 128 + deep_gemm are the M3 // SM100 auto-defaults on current main, so this is also the bare-launch // behavior; they engage MiniMax's MSA sparse-attention kernel (fmha_sm100, - // pre-installed in the dev-minimax-m3 images; see Configuration Tips), Triton + // pre-installed in lmsysorg/sglang:latest; see Configuration Tips), Triton // fallback otherwise. // AMD: tp8. MI350X/MI355X (gfx950) serve MXFP8 natively (backends auto). MI300X/ // MI325X (gfx942) need --attention-backend aiter + --moe-runner-backend triton, diff --git a/docs_new/src/snippets/configs/poolside/laguna-m1.jsx b/docs_new/src/snippets/configs/poolside/laguna-m1.jsx index 0c60fb3e0..99dc2b22e 100644 --- a/docs_new/src/snippets/configs/poolside/laguna-m1.jsx +++ b/docs_new/src/snippets/configs/poolside/laguna-m1.jsx @@ -100,16 +100,14 @@ sgl-eval run gsm8k \\ ["gsm8k_pct", "GSM8K", "%"], ], - // Pinned nightly with the Laguna-M.1 build (PR #28400 + #28604 + #28649; cu13 covers H200 + all Blackwell). - // dev-cu13-618-nightly was generated after the FP8 g_proj fix (#28649) landed, so it serves FP8 too. - // (Equivalent pip nightly: 0.5.14.dev20260618+g97e3b8998d.) Blackwell FP8 additionally needs the - // --fp8-gemm-backend triton flag (in those cells) until PR #28662 merges. + // lmsysorg/sglang:latest (cu13) covers H200 + all Blackwell and carries the + // Laguna-M.1 build (PR #28400 + #28604 + #28649, incl. the FP8 g_proj fix). dockerImages: { - h200: "lmsysorg/sglang:dev-cu13-618-nightly", - b200: "lmsysorg/sglang:dev-cu13-618-nightly", - b300: "lmsysorg/sglang:dev-cu13-618-nightly", - gb200: "lmsysorg/sglang:dev-cu13-618-nightly", - gb300: "lmsysorg/sglang:dev-cu13-618-nightly", + h200: "lmsysorg/sglang:latest", + b200: "lmsysorg/sglang:latest", + b300: "lmsysorg/sglang:latest", + gb200: "lmsysorg/sglang:latest", + gb300: "lmsysorg/sglang:latest", }, github: { @@ -232,7 +230,7 @@ sgl-eval run gsm8k \\ }, { // VERIFIED on 8xH200 (FP8, tp8): GSM8K 93.25%. FP8 needs the g_proj fix (PR #28649, MERGED) on - // top of #28400+#28604 — the pinned dev-cu13-618-nightly image has it. Hopper does NOT hit the + // top of #28400+#28604 — lmsysorg/sglang:latest has it. Hopper does NOT hit the // Blackwell DeepGEMM UE8M0 issue, so no --fp8-gemm-backend flag here. match: { hw: "h200", variant: "default", quant: "fp8", strategy: "balanced", nodes: "single" }, verified: true, diff --git a/docs_new/src/snippets/configs/poolside/laguna-xs21.jsx b/docs_new/src/snippets/configs/poolside/laguna-xs21.jsx index 4f88be2b5..8267b9d76 100644 --- a/docs_new/src/snippets/configs/poolside/laguna-xs21.jsx +++ b/docs_new/src/snippets/configs/poolside/laguna-xs21.jsx @@ -142,11 +142,11 @@ sgl-eval run aime25 \\ ["aime25_pct", "AIME25", "%"], ], - // Dedicated image built for this cookbook page (PR #29446 + #29761 preinstalled on cu13). + // lmsysorg/sglang:latest (cu13) carries the Laguna-XS.2.1 build (PR #29446 + #29761). dockerImages: { - h200: "lmsysorg/sglang:dev-cu13-laguna-xs-2-1", - b300: "lmsysorg/sglang:dev-cu13-laguna-xs-2-1", - gb300: "lmsysorg/sglang:dev-cu13-laguna-xs-2-1", + h200: "lmsysorg/sglang:latest", + b300: "lmsysorg/sglang:latest", + gb300: "lmsysorg/sglang:latest", }, github: {