| # Dockerfiles of verl |
|
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| We provide pre-built Docker images for quick setup. And from this version, we utilize a new image release hierarchy for productivity and stability. |
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| Start from v0.6.0, we use vllm and sglang release image as our base image. |
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| Start from v0.7.0, since vllm/vllm-openai:v0.12.0 is a minimal image without some essential libraries, we use nvidia/cuda:12.9.1-devel-ubuntu22.04 as our base image for vllm. |
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|
| ## Base Image |
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| - vLLM: https://hub.docker.com/r/nvidia/cuda |
| - SGLang: https://hub.docker.com/r/lmsysorg/sglang |
|
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| ## Application Image |
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| Upon base image, the following packages are added: |
| - flash_attn |
| - Megatron-LM |
| - Apex |
| - TransformerEngine |
| - DeepEP |
| |
| Latest docker file: |
| - [Dockerfile.stable.vllm](https://github.com/volcengine/verl/blob/main/docker/Dockerfile.stable.vllm) |
| - [Dockerfile.stable.sglang](https://github.com/volcengine/verl/blob/main/docker/Dockerfile.stable.sglang) |
| |
| All pre-built images are available in dockerhub: https://hub.docker.com/r/verlai/verl. For example, `verlai/verl:sgl059.latest`, `verlai/verl:vllm017.latest`. |
| |
| You can find the latest images used for development and ci in our github workflows: |
| - [.github/workflows/vllm.yml](https://github.com/volcengine/verl/blob/main/.github/workflows/vllm.yml) |
| - [.github/workflows/sgl.yml](https://github.com/volcengine/verl/blob/main/.github/workflows/sgl.yml) |
| |
| |
| ## Installation from Docker |
| |
| After pulling the desired Docker image and installing desired inference and training frameworks, you can run it with the following steps: |
| |
| 1. Launch the desired Docker image and attach into it: |
| |
| ```sh |
| docker create --runtime=nvidia --gpus all --net=host --shm-size="10g" --cap-add=SYS_ADMIN -v .:/workspace/verl --name verl <image:tag> sleep infinity |
| docker start verl |
| docker exec -it verl bash |
| ``` |
| |
| 2. If you use the images provided, you only need to install verl itself without dependencies: |
| |
| ```sh |
| # install the nightly version (recommended) |
| git clone https://github.com/volcengine/verl && cd verl |
| pip3 install --no-deps -e . |
| ``` |
| |
| [Optional] If you hope to switch between different frameworks, you can install verl with the following command: |
| |
| ```sh |
| # install the nightly version (recommended) |
| git clone https://github.com/volcengine/verl && cd verl |
| pip3 install -e .[vllm] |
| pip3 install -e .[sglang] |
| ``` |
| |
| ## Release History |
| |
| - 2026/03/10: update vllm stable image to vllm==0.17.0; update sglang stable image to sglang==0.5.9 |
| - 2026/01/17: update vllm stable image to torch==2.9.1, cudnn==9.16, deepep==1.2.1 |
| - 2025/12/23: update vllm stable image to vllm==0.12.0; update sglang stable image to sglang==0.5.6 |
| - 2025/11/18: update vllm stable image to vllm==0.11.1; update sglang stable image to sglang==0.5.5 |
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