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Signed-off-by: Gal Hubara Agam <96368689+galagam@users.noreply.github.com> Signed-off-by: Neta Zmora <96238833+nzmora-nvidia@users.noreply.github.com> Signed-off-by: Lucas Liebenwein <11156568+lucaslie@users.noreply.github.com> Signed-off-by: nvchenghaoz <211069071+nvchenghaoz@users.noreply.github.com> Signed-off-by: Frida Hou <201670829+Fridah-nv@users.noreply.github.com> Signed-off-by: greg-kwasniewski1 <213329731+greg-kwasniewski1@users.noreply.github.com> Signed-off-by: Suyog Gupta <41447211+suyoggupta@users.noreply.github.com> Co-authored-by: Gal Hubara-Agam <96368689+galagam@users.noreply.github.com> Co-authored-by: Neta Zmora <nzmora@nvidia.com> Co-authored-by: nvchenghaoz <211069071+nvchenghaoz@users.noreply.github.com> Co-authored-by: Frida Hou <201670829+Fridah-nv@users.noreply.github.com> Co-authored-by: Suyog Gupta <41447211+suyoggupta@users.noreply.github.com> Co-authored-by: Grzegorz Kwasniewski <213329731+greg-kwasniewski1@users.noreply.github.com> |
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| README.md | ||
TensorRT-LLM Benchmarks
Overview
There are currently two workflows to benchmark TensorRT-LLM:
trtllm-benchtrtllm-benchis native to TensorRT-LLM and is a Python benchmarker for reproducing and testing the performance of TensorRT-LLM.- NOTE: This benchmarking suite is a current work in progress and is prone to large changes.
- C++ benchmarks
- The recommended workflow that uses TensorRT-LLM C++ API and can take advantage of the latest features of TensorRT-LLM.