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TensorRT-LLMs/docs/source/installation/linux.md
Zhanrui Sun 776bb25bfd
[TRTLLM-8658][infra] upgrade to DLFW 25.10 and pytorch 2.9.0 / triton 3.5.0 (#8621) 
Signed-off-by: ZhanruiSunCh <184402041+ZhanruiSunCh@users.noreply.github.com>
Signed-off-by: Zhanrui Sun <184402041+ZhanruiSunCh@users.noreply.github.com>
Signed-off-by: Yanchao Lu <yanchaol@nvidia.com>
Co-authored-by: Yanchao Lu <yanchaol@nvidia.com>
2025-11-03 09:24:58 +08:00

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(linux)=

Installing on Linux via pip

  1. Install TensorRT LLM (tested on Ubuntu 24.04).

    Install prerequisites

    Before the pre-built Python wheel can be installed via pip, a few prerequisites must be put into place:

    Install CUDA Toolkit following the CUDA Installation Guide for Linux and make sure CUDA_HOME environment variable is properly set.

    # By default, PyTorch CUDA 12.8 package is installed. Install PyTorch CUDA 13.0 package to align with the CUDA version used for building TensorRT LLM wheels.
pip3 install torch==2.9.0 torchvision --index-url https://download.pytorch.org/whl/cu130

sudo apt-get -y install libopenmpi-dev

    Instead of manually installing the preqrequisites as described
above, it is also possible to use the pre-built [TensorRT LLM Develop container
image hosted on NGC](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/tensorrt-llm/containers/devel)
(see [here](containers) for information on container tags).

    Install pre-built TensorRT LLM wheel

    Once all prerequisites are in place, TensorRT LLM can be installed as follows:

    pip3 install --upgrade pip setuptools && pip3 install tensorrt_llm

    This project will download and install additional third-party open source software projects. Review the license terms of these open source projects before use.

  2. Sanity check the installation by running the following in Python (tested on Python 3.12):

        :language: python
    :linenos:

Known limitations

There are some known limitations when you pip install pre-built TensorRT LLM wheel package.

  1. MPI in the Slurm environment

    If you encounter an error while running TensorRT LLM in a Slurm-managed cluster, you need to reconfigure the MPI installation to work with Slurm. The setup methods depends on your slurm configuration, pls check with your admin. This is not a TensorRT LLM specific, rather a general mpi+slurm issue.

    The application appears to have been direct launched using "srun",
but OMPI was not built with SLURM support. This usually happens
when OMPI was not configured --with-slurm and we weren't able
to discover a SLURM installation in the usual places.