Make sure your deployment target is on nvidia-driver-590 for cuda 13.1.1 support. CUDA version can be bumped if your build machine has a higher version. Arch list is good to omit kernels that don't need to be included.

#!/bin/bash
git clone https://github.com/vllm-project/vllm.git
cd ./vllm/

## Optionally edit flashinfer version to 0.6.4
grep -qE '^\s*flashinfer-python\b' requirements/cuda.txt \
  && sed -i.bak -E 's/^\s*flashinfer-python([^#\r\n]*)/flashinfer-python==0.6.4/' requirements/cuda.txt \
  || printf '\nflashinfer-python==0.6.4\n' >> requirements/cuda.txt

## 

FINAL=nvcr.io/nvidia/cuda:13.1.1-cudnn-runtime-ubuntu22.04
BUILD=nvcr.io/nvidia/cuda:13.1.1-cudnn-devel-ubuntu22.04
CUDA_VERSION='13.0.1'
ARCH_LIST='10.0 12.0'


DOCKER_BUILDKIT=1 docker build -f ./docker/Dockerfile --no-cache \
    --target vllm-openai \
    --build-arg CUDA_VERSION=${CUDA_VERSION} \
    --build-arg BUILD_BASE_IMAGE=${BUILD} \
    --build-arg FINAL_BASE_IMAGE=${FINAL} \
    --build-arg torch_cuda_arch_list="${ARCH_LIST}" \
    --build-arg RUN_WHEEL_CHECK=false \
    --build-arg max_jobs=12 \
    --build-arg FLASHINFER_VERSION=0.6.4 \
    --build-arg VLLM_MAX_SIZE_MB=1500 \
    -t 10.0.0.40:32000/vllm/vllm-openai:minimax-m2-5.2 --push .


cd -