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Update vLLM container version to 25.11-py3

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Ev Lacey 2025-12-02 16:25:52 -08:00 committed by GitHub
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nvidia/vllm/README.md
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@ -57,9 +57,9 @@ support for ARM64.
## Step 1. Pull vLLM container image ## Step 1. Pull vLLM container image
Find the latest container build from https://catalog.ngc.nvidia.com/orgs/nvidia/containers/vllm?version=25.09-py3 Find the latest container build from https://catalog.ngc.nvidia.com/orgs/nvidia/containers/vllm?version=25.11-py3
``` ```
docker pull nvcr.io/nvidia/vllm:25.09-py3 docker pull nvcr.io/nvidia/vllm:25.11-py3
``` ```
## Step 2. Test vLLM in container ## Step 2. Test vLLM in container
@ -68,7 +68,7 @@ Launch the container and start vLLM server with a test model to verify basic fun
```bash ```bash
docker run -it --gpus all -p 8000:8000 \ docker run -it --gpus all -p 8000:8000 \
nvcr.io/nvidia/vllm:25.09-py3 \ nvcr.io/nvidia/vllm:25.11-py3 \
vllm serve "Qwen/Qwen2.5-Math-1.5B-Instruct" vllm serve "Qwen/Qwen2.5-Math-1.5B-Instruct"
``` ```
@ -96,7 +96,7 @@ Expected response should contain `"content": "204"` or similar mathematical calc
For container approach (non-destructive): For container approach (non-destructive):
```bash ```bash
docker rm $(docker ps -aq --filter ancestor=nvcr.io/nvidia/vllm:25.09-py3) docker rm $(docker ps -aq --filter ancestor=nvcr.io/nvidia/vllm:25.11-py3)
docker rmi nvcr.io/nvidia/vllm docker rmi nvcr.io/nvidia/vllm
``` ```
@ -150,8 +150,8 @@ After this, you should be able to run docker commands without using `sudo`.
```bash ```bash
docker pull nvcr.io/nvidia/vllm:25.09-py3 docker pull nvcr.io/nvidia/vllm:25.11-py3
export VLLM_IMAGE=nvcr.io/nvidia/vllm:25.09-py3 export VLLM_IMAGE=nvcr.io/nvidia/vllm:25.11-py3
``` ```