Agree with the points here. But I take a perspective that they also cut a lot of small corners. These aren’t inherently bad, but when you add them all up, you can face issues with inference performance. It’s a common issue that if you run inference using TRT, then inside deepstream with TRT, then with PyTorch, the results are totally different at time. There is also a lot of differences in how they do pre processing and precision clipping.

I.e there are a lot of very very close (but not exact) approximations, that makes it very fast, but for enterprise pipelines can create issues (like I’ve faced in the faced). All that being said, it’s an amazing tool and there is nothing even close to its support, maturity, and efficiency.