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
2e8f453fa8288e6dbf8394cf99c4e1b768307abcfe93933d3648a1d53646e5d9CONFIG
Entrypoint /opt/nvidia/nvidia_entrypoint.sh; WorkingDir /app/tensorrt_llm; ExposedPorts 6006/tcp, 8888/tcp
06/27/2026 4:41 PM UTC
61686aa18180436755f949a70e8bea996d24a791297fd2343446de21a0058c23ENV
TRT_LLM_GIT_COMMIT=c25c23f71786bad54d192893d696ce8043426eca TRT_LLM_VERSION=1.3.0rc20
06/27/2026 4:41 PM UTC
9f9fff09bfa7065519796eab4c61afb7472c609e61179e2171ee28cff33d8710ARG
TARGETARCH=amd64
06/27/2026 4:41 PM UTC
664bc65329b1611de8bdaec95410303cdb826a2df7fb059363d9ddf4d4630280ARG
TRT_LLM_VER=1.3.0rc20
06/27/2026 4:41 PM UTC
9587922223f8f8b77e4ed0ced88b28bba16082b8c67f347cea620a9a0cbeeedcARG
GIT_COMMIT=c25c23f71786bad54d192893d696ce8043426eca
06/27/2026 4:41 PM UTC
ba93442fca69d8b587c5040064bc8bee7df85f961546f3535a7bac434eaffa7aRUN
/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 $(python3 -c 'import site; print(f"{site.getsitepackages()[0]}/tensorrt_llm/libs")') lib &&
  test -f lib/libnvinfer_plugin_tensorrt_llm.so &&
  echo "/app/tensorrt_llm/lib" > /etc/ld.so.conf.d/tensorrt_llm.conf &&
  ldconfig &&
  ! ( ldd -v bin/executorWorker | grep tensorrt_llm | grep -q "not found" ) &&
  rm -rf /root/.cache/uv/archive-v0 &&
  rm -rf /usr/local/lib/python3.12/dist-packages/setuptools/_vendor/jaraco.context-5.3.0.dist-info &&
  rm -rf /usr/local/lib/python3.12/dist-packages/setuptools/_vendor/wheel-0.45.1.dist-info
06/27/2026 4:41 PM UTC
b8928978010387b65ca7b74908a14efc2dcb7ecc2b80196f188b29154bcde482RUN
/bin/bash -c pip install /tmp/wheel/tensorrt_llm*.whl
06/27/2026 4:41 PM UTC
028605d7673fe10e2488e34af567ec9b1955c9e43a4be7c4c59d409c3f3ab1d4WORKDIR
/app/tensorrt_llm
06/27/2026 4:34 PM UTC
4f1b5487d048f16626e455d2e67dfc7f435c533b24db490add925fb5384e2cc6RUN
SH_ENV=/etc/shinit_v2 BASH_ENV=/etc/bash.bashrc GITHUB_MIRROR=https://urm.nvidia.com/artifactory/github-go-remote PYTHON_VERSION=3.12.3 TRT_VER= CUDA_VER= CUDNN_VER= NCCL_VER= CUBLAS_VER= TORCH_INSTALL_TYPE=skip TRT_LLM_VER=1.3.0rc20 TARGETARCH=amd64 /bin/bash -c bash /tmp/gen_attribution.sh "devel" "${TRT_LLM_VER}" "${TARGETARCH}"
06/27/2026 4:29 PM UTC
5ff137e4266c4f7d0ad182a1c75d28205977f5d629332845b345798cd03bec80ARG
TARGETARCH=amd64
06/27/2026 4:29 PM UTC
...

NVIDIA uses cookies to improve your experience on our web site. We and our third-party partners also use cookies and other tools to collect and record information you provide as well as information about your interactions with our websites for performance improvement, analytics, and to assist in marketing efforts. By clicking "Accept All", you consent to our use of cookies and other tools as described in our Cookie Policy. You can manage your cookie settings by clicking on "Manage Settings." By continuing to use this site or by clicking one of the buttons below, you agree to our Terms of Service (which contains important waivers). Please see our Privacy Policy for more information on our privacy practices.