NVIDIA
NVIDIA
TensorRT LLM Release
Container
NVIDIA
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
sha256:4b4839d006d5fb9e5f4cb13e0d2d95aa21ebbc919e53cfae6ff8562100119165RUN
GIT_COMMIT=c25c23f71786bad54d192893d696ce8043426eca TRT_LLM_VER=1.3.0rc20 TARGETARCH=amd64 /bin/bash -c bash /mnt/gen_attribution.sh "release" "${TRT_LLM_VER}" "${TARGETARCH}"
06/27/2026 4:41 PM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ENV
TRT_LLM_GIT_COMMIT=c25c23f71786bad54d192893d696ce8043426eca TRT_LLM_VERSION=1.3.0rc20
06/27/2026 4:41 PM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
TARGETARCH=amd64
06/27/2026 4:41 PM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
TRT_LLM_VER=1.3.0rc20
06/27/2026 4:41 PM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
GIT_COMMIT=c25c23f71786bad54d192893d696ce8043426eca
06/27/2026 4:41 PM UTC
sha256:429fc3fc6e7c04bb0034966e5f690563a9997d99cde953f4e127fb656c6457f0RUN
/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 $(python3 -c 'import site; print(f"{site.getsitepackages()[0]}/tensorrt_llm/libs")') lib &&
  test -f lib/libnvinfer_plugin_tensorrt_llm.so &&
  echo "/app/tensorrt_llm/lib" > /etc/ld.so.conf.d/tensorrt_llm.conf &&
  ldconfig &&
  ! ( ldd -v bin/executorWorker | grep tensorrt_llm | grep -q "not found" ) &&
  rm -rf /root/.cache/uv/archive-v0 &&
  rm -rf /usr/local/lib/python3.12/dist-packages/setuptools/_vendor/jaraco.context-5.3.0.dist-info &&
  rm -rf /usr/local/lib/python3.12/dist-packages/setuptools/_vendor/wheel-0.45.1.dist-info
06/27/2026 4:41 PM UTC
sha256:8ea55428762eccebe0e9ba8e5a3edb31cb4aa029daf45011d0523c9a198fc4e2RUN
/bin/bash -c pip install /tmp/wheel/tensorrt_llm*.whl
06/27/2026 4:41 PM UTC
sha256:7494b822f0a6957b15e25eea57d5ad195a1973fca9cd787afa6377e6d367585cWORKDIR
/app/tensorrt_llm
06/27/2026 4:34 PM UTC
sha256:7c7011ba5e6010cea0686874892b03dcbc553c93682b7e92cc57cd390b18eafaRUN
SH_ENV=/etc/shinit_v2 BASH_ENV=/etc/bash.bashrc GITHUB_MIRROR=https://urm.nvidia.com/artifactory/github-go-remote PYTHON_VERSION=3.12.3 TRT_VER= CUDA_VER= CUDNN_VER= NCCL_VER= CUBLAS_VER= TORCH_INSTALL_TYPE=skip TRT_LLM_VER=1.3.0rc20 TARGETARCH=amd64 /bin/bash -c bash /tmp/gen_attribution.sh "devel" "${TRT_LLM_VER}" "${TARGETARCH}"
06/27/2026 4:29 PM UTC
sha256:a3ed95caeb02ffe68cdd9fd84406680ae93d633cb16422d00e8a7c22955b46d4ARG
TARGETARCH=amd64
06/27/2026 4:29 PM UTC
...

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