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  • NVIDIA
    TensorRT LLM Release
    Container
    NVIDIA
    TensorRT LLM Release

    TensorRT LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and supports state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs.

  • LayerLabelCreated
    sha256:444106b870104487f83bf5fd4e50749b738efddc6c33e170219f627e16d2bba5RUN
    GIT_COMMIT=15d06c0923b63ac1781784d5f59e1747bb47d5f1 TRT_LLM_VER=1.3.0rc18 TARGETARCH=amd64 /bin/bash -c bash /mnt/gen_attribution.sh "release" "${TRT_LLM_VER}" "${TARGETARCH}"
    		06/08/2026 5:18 PM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ENV
    TRT_LLM_GIT_COMMIT=15d06c0923b63ac1781784d5f59e1747bb47d5f1 TRT_LLM_VERSION=1.3.0rc18
    		06/08/2026 5:18 PM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
    TARGETARCH=amd64
    		06/08/2026 5:18 PM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
    TRT_LLM_VER=1.3.0rc18
    		06/08/2026 5:18 PM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
    GIT_COMMIT=15d06c0923b63ac1781784d5f59e1747bb47d5f1
    		06/08/2026 5:18 PM UTC
    sha256:f8b2a450ba5d8d9fbf85300c8db12c5543389cc277fa491a05b4c1d87f2dde8bRUN
    /bin/bash -c cp /mnt/ctx/README.md ./ &&
  cp -r /mnt/ctx/docs ./docs &&
  cp -r /mnt/ctx/include ./include &&
  cp -r /mnt/ctx/examples ./examples &&
  chmod -R a+w examples &&
  cp /mnt/wheel/tensorrt_llm*.whl ./ &&
  cp -r /mnt/benchmarks ./benchmarks &&
  mkdir -p benchmarks/cpp &&
  cp /mnt/cpp_benchmarks/bertBenchmark /mnt/cpp_benchmarks/gptManagerBenchmark /mnt/cpp_benchmarks/disaggServerBenchmark benchmarks/cpp/ &&
  rm -v benchmarks/cpp/bertBenchmark.cpp benchmarks/cpp/gptManagerBenchmark.cpp benchmarks/cpp/disaggServerBenchmark.cpp benchmarks/cpp/CMakeLists.txt &&
  ln -sv $(python3 -c 'import site; print(f"{site.getsitepackages()[0]}/tensorrt_llm/bin")') bin &&
  test -f bin/executorWorker &&
  ln -sv $(python3 -c 'import site; print(f"{site.getsitepackages()[0]}/tensorrt_llm/libs")') lib &&
  test -f lib/libnvinfer_plugin_tensorrt_llm.so &&
  echo "/app/tensorrt_llm/lib" > /etc/ld.so.conf.d/tensorrt_llm.conf &&
  ldconfig &&
  ! ( ldd -v bin/executorWorker | grep tensorrt_llm | grep -q "not found" ) &&
  rm -rf /root/.cache/uv/archive-v0 &&
  rm -rf /usr/local/lib/python3.12/dist-packages/setuptools/_vendor/jaraco.context-5.3.0.dist-info &&
  rm -rf /usr/local/lib/python3.12/dist-packages/setuptools/_vendor/wheel-0.45.1.dist-info
    		06/08/2026 5:18 PM UTC
    sha256:7ec8d9901540531059e44ce842178cfacafdfc5ec053a2d5199dc81298368fb0RUN
    /bin/bash -c pip install /tmp/wheel/tensorrt_llm*.whl
    		06/08/2026 5:18 PM UTC
    sha256:21d6c86137e81fe699cddb5dc015765b4b24a6adfc35016d163c2f6029f8d8c3WORKDIR
    /app/tensorrt_llm
    		06/08/2026 5:07 PM UTC
    sha256:906aef250c7dcf092c56f83b5279561e39e7d20024f77db8d8041bfacb94a999RUN
    SH_ENV=/etc/shinit_v2 BASH_ENV=/etc/bash.bashrc GITHUB_MIRROR=https://urm.nvidia.com/artifactory/github-go-remote PYTHON_VERSION=3.12.3 TRT_VER= CUDA_VER= CUDNN_VER= NCCL_VER= CUBLAS_VER= TORCH_INSTALL_TYPE=skip TRT_LLM_VER=1.3.0rc18 TARGETARCH=amd64 /bin/bash -c bash /tmp/gen_attribution.sh "devel" "${TRT_LLM_VER}" "${TARGETARCH}"
    		06/08/2026 5:03 PM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
    TARGETARCH=amd64
    		06/08/2026 5:03 PM UTC
    ...