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<p class="caption" role="heading"><span class="caption-text">Getting Started</span></p>
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<li class="toctree-l1"><a class="reference internal" href="../advanced/gpt-attention.html">Multi-Head, Multi-Query, and Group-Query Attention</a></li>
<li class="toctree-l1"><a class="reference internal" href="../advanced/gpt-runtime.html">C++ GPT Runtime</a></li>
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<li class="toctree-l1"><a class="reference internal" href="../reference/memory.html">Memory Usage of TensorRT-LLM</a></li>
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<p class="caption" role="heading"><span class="caption-text">Blogs</span></p>
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<li class="toctree-l1"><a class="reference internal" href="../blogs/H100vsA100.html">H100 has 4.6x A100 Performance in TensorRT-LLM, achieving 10,000 tok/s at 100ms to first token</a></li>
<li class="toctree-l1"><a class="reference internal" href="../blogs/H200launch.html">H200 achieves nearly 12,000 tokens/sec on Llama2-13B with TensorRT-LLM</a></li>
<li class="toctree-l1"><a class="reference internal" href="../blogs/Falcon180B-H200.html">Falcon-180B on a single H200 GPU with INT4 AWQ, and 6.7x faster Llama-70B over A100</a></li>
<li class="toctree-l1"><a class="reference internal" href="../blogs/quantization-in-TRT-LLM.html">Speed up inference with SOTA quantization techniques in TRT-LLM</a></li>
<li class="toctree-l1"><a class="reference internal" href="../blogs/XQA-kernel.html">New XQA-kernel provides 2.4x more Llama-70B throughput within the same latency budget</a></li>
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<section id="installing-on-windows">
<span id="windows"></span><h1>Installing on Windows<a class="headerlink" href="#installing-on-windows" title="Link to this heading"></a></h1>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>The Windows release of TensorRT-LLM is currently in beta.
We recommend checking out the <a class="reference external" href="https://github.com/NVIDIA/TensorRT-LLM/releases/tag/v0.16.0">v0.16.0 tag</a> for the most stable experience.</p>
</div>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>TensorRT-LLM on Windows only supports single-GPU execution.</p>
</div>
<p><strong>Prerequisites</strong></p>
<ol class="arabic">
<li><p>Clone this repository using <a class="reference external" href="https://git-scm.com/download/win">Git for Windows</a>.</p></li>
<li><p>Install the dependencies one of two ways:</p>
<ol class="arabic">
<li><p>Install all dependencies together.</p>
<ol class="arabic simple">
<li><p>Run the provided PowerShell script <code class="docutils literal notranslate"><span class="pre">setup_env.ps1</span></code> located under the <code class="docutils literal notranslate"><span class="pre">/windows/</span></code> folder which installs Python and CUDA 12.6.3 automatically with default settings. Run PowerShell as Administrator to use the script.</p></li>
</ol>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>./setup_env.ps1<span class="w"> </span><span class="o">[</span>-skipCUDA<span class="o">]</span><span class="w"> </span><span class="o">[</span>-skipPython<span class="o">]</span>
</pre></div>
</div>
<ol class="arabic simple" start="2">
<li><p>Close and re-open any existing PowerShell or Git Bash windows so they pick up the new <code class="docutils literal notranslate"><span class="pre">Path</span></code> modified by the <code class="docutils literal notranslate"><span class="pre">setup_env.ps1</span></code> script above.</p></li>
</ol>
</li>
<li><p>Install the dependencies one at a time.</p>
<ol class="arabic simple">
<li><p>Install <a class="reference external" href="https://www.python.org/ftp/python/3.10.11/python-3.10.11-amd64.exe">Python 3.10</a>.</p>
<ol class="arabic simple">
<li><p>Select <strong>Add python.exe to PATH</strong> at the start of the installation. The installation may only add the <code class="docutils literal notranslate"><span class="pre">python</span></code> command, but not the <code class="docutils literal notranslate"><span class="pre">python3</span></code> command.</p></li>
<li><p>Navigate to the installation path <code class="docutils literal notranslate"><span class="pre">%USERPROFILE%\AppData\Local\Programs\Python\Python310</span></code> (<code class="docutils literal notranslate"><span class="pre">AppData</span></code> is a hidden folder) and copy <code class="docutils literal notranslate"><span class="pre">python.exe</span></code> to <code class="docutils literal notranslate"><span class="pre">python3.exe</span></code>.</p></li>
</ol>
</li>
<li><p>Install <a class="reference external" href="https://developer.nvidia.com/cuda-12-6-3-download-archive?target_os=Windows&amp;amp;target_arch=x86_64">CUDA 12.6.3 Toolkit</a>. Use the Express Installation option. Installation may require a restart.</p></li>
</ol>
</li>
</ol>
</li>
<li><p>If using conda environment, run the following command before installing TensorRT-LLM.</p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>conda<span class="w"> </span>install<span class="w"> </span>-c<span class="w"> </span>conda-forge<span class="w"> </span>pyarrow
</pre></div>
</div>
</li>
</ol>
<p><strong>Steps</strong></p>
<ol class="arabic simple">
<li><p>Install TensorRT-LLM.</p></li>
</ol>
<p>If you have an existing TensorRT installation (from older versions of <code class="docutils literal notranslate"><span class="pre">tensorrt_llm</span></code>), please execute</p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>pip<span class="w"> </span>uninstall<span class="w"> </span>-y<span class="w"> </span>tensorrt<span class="w"> </span>tensorrt_libs<span class="w"> </span>tensorrt_bindings
pip<span class="w"> </span>uninstall<span class="w"> </span>-y<span class="w"> </span>nvidia-cublas-cu12<span class="w"> </span>nvidia-cuda-nvrtc-cu12<span class="w"> </span>nvidia-cuda-runtime-cu12<span class="w"> </span>nvidia-cudnn-cu12
</pre></div>
</div>
<p>before installing TensorRT-LLM with the following command.</p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>pip<span class="w"> </span>install<span class="w"> </span><span class="nv">tensorrt_llm</span><span class="o">==</span><span class="m">0</span>.16.0<span class="w"> </span>--extra-index-url<span class="w"> </span>https://download.pytorch.org/whl/
</pre></div>
</div>
<p>Run the following command to verify that your TensorRT-LLM installation is working properly.</p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>python<span class="w"> </span>-c<span class="w"> </span><span class="s2">&quot;import tensorrt_llm; print(tensorrt_llm._utils.trt_version())&quot;</span>
</pre></div>
</div>
<ol class="arabic simple" start="2">
<li><p>Build the model.</p></li>
<li><p>Deploy the model.</p></li>
</ol>
<p><strong>Known Issue</strong></p>
<ol class="arabic simple">
<li><p><code class="docutils literal notranslate"><span class="pre">OSError:</span> <span class="pre">exception:</span> <span class="pre">access</span> <span class="pre">violation</span> <span class="pre">reading</span> <span class="pre">0x0000000000000000</span></code> during <code class="docutils literal notranslate"><span class="pre">import</span> <span class="pre">tensorrt_llm</span></code> or <code class="docutils literal notranslate"><span class="pre">trtllm-build</span></code>.</p></li>
</ol>
<p>This may be caused by an outdated Microsoft Visual C++ Redistributable Version. Please install
<a class="reference external" href="https://learn.microsoft.com/en-us/cpp/windows/latest-supported-vc-redist?view=msvc-170#latest-microsoft-visual-c-redistributable-version">the latest MSVC</a>
and retry. Check the system path to make sure the latest version installed in <code class="docutils literal notranslate"><span class="pre">System32</span></code> is searched first. Check dependencies to make sure no other packages are using an outdated version (e.g. package <code class="docutils literal notranslate"><span class="pre">pyarrow</span></code> might contain an outdated MSVC DLL).</p>
<ol class="arabic simple" start="2">
<li><p>OSError: [WinError 126] The specified module could not be found. Error loading “…\Lib\site-packages\torch\lib\fbgemm.dll” or one of its dependencies.</p></li>
</ol>
<p>Installing the latest [Build Tools for Visual Studio 2022] (https://visualstudio.microsoft.com/downloads/#build-tools-for-visual-studio-2022) will resolve the issue.</p>
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