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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
    sha256:2f18fb94c9f3377f5ad3bc37cb4f55a2205b0d1f7261d560f9940bfb20ee721aRUN
    GIT_COMMIT=1662a877f374ee944d1907e8efa735d35ff2abf6 TRT_LLM_VER=1.3.0rc21 TARGETARCH=amd64 /bin/bash -c bash /mnt/gen_attribution.sh "release" "${TRT_LLM_VER}" "${TARGETARCH}"
    		07/14/2026 3:57 PM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ENV
    TRT_LLM_GIT_COMMIT=1662a877f374ee944d1907e8efa735d35ff2abf6 TRT_LLM_VERSION=1.3.0rc21
    		07/14/2026 3:57 PM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
    TARGETARCH=amd64
    		07/14/2026 3:57 PM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
    TRT_LLM_VER=1.3.0rc21
    		07/14/2026 3:57 PM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
    GIT_COMMIT=1662a877f374ee944d1907e8efa735d35ff2abf6
    		07/14/2026 3:57 PM UTC
    sha256:06132436d64ac4ba0dc11741da9069b79ea3523f25d869fecd255a4200542a84RUN
    /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 $(python3 -c 'import site; print(f"{site.getsitepackages()[0]}/tensorrt_llm/libs")') lib &&
  test -f lib/libnvinfer_plugin_tensorrt_llm.so &&
  echo "/app/tensorrt_llm/lib" > /etc/ld.so.conf.d/tensorrt_llm.conf &&
  ldconfig &&
  ! ( ldd -v bin/executorWorker | grep tensorrt_llm | grep -q "not found" ) &&
  rm -rf /root/.cache/uv/archive-v0 &&
  rm -rf /usr/local/lib/python3.12/dist-packages/setuptools/_vendor/jaraco.context-5.3.0.dist-info &&
  rm -rf /usr/local/lib/python3.12/dist-packages/setuptools/_vendor/wheel-0.45.1.dist-info
    		07/14/2026 3:57 PM UTC
    sha256:22fa80b89afedb457a4b24dbfa08c173f9dfca8eece0172c4fafdfe1da6c436cRUN
    /bin/bash -c pip install /tmp/wheel/tensorrt_llm*.whl
    		07/14/2026 3:57 PM UTC
    sha256:0cd9026dc478e772b13bbb20db1dfd956544d32be4b4be3d31029807e4e03dcdWORKDIR
    /app/tensorrt_llm
    		07/14/2026 3:53 PM UTC
    sha256:d04e526a86772124120272d6d7ffae3a419c4a43b34383a8906cb6eeed16b348RUN
    SH_ENV=/etc/shinit_v2 BASH_ENV=/etc/bash.bashrc GITHUB_MIRROR=https://urm.nvidia.com/artifactory/github-go-remote PYTHON_VERSION=3.12.3 TRT_VER= CUDA_VER= CUDNN_VER= NCCL_VER= CUBLAS_VER= TORCH_INSTALL_TYPE=skip TRT_LLM_VER=1.3.0rc21 TARGETARCH=amd64 /bin/bash -c bash /tmp/gen_attribution.sh "devel" "${TRT_LLM_VER}" "${TARGETARCH}"
    		07/14/2026 3:49 PM UTC
    sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
    TARGETARCH=amd64
    		07/14/2026 3:49 PM UTC
    ...