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INT8 Quantization of dinov2 TensorRT Model is Not Faster than FP16 Quantization #489

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mr-lz opened this issue Dec 6, 2024 · 0 comments

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@mr-lz
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mr-lz commented Dec 6, 2024

Hello,

I used PyTorch-Quantization for post-training INT8 quantization on the dinov2-base model and then converted it to a TensorRT model. However, I found that the INT8 model is slightly slower than the FP16 model (the same conclusion was observed on A100, V100, and A10). Is this behavior normal?

Thank you.

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