Free NVIDIA NCA-AIIO Actual Exam Questions - Question 11 Discussion
each trained using different frameworks (e.g., TensorFlow, PyTorch, and ONNX). You need a
deployment solution that can efficiently serve all these models in production, regardless of the
framework they were built in. Which software component should you choose?
Maybe D – it’s designed to serve models from various frameworks without extra conversion steps, unlike B which mainly focuses on optimization rather than serving multiple frameworks directly.
B imo, TensorRT optimizes models from different frameworks for faster inference.
Makes sense to go with D since Triton supports serving models from TensorFlow, PyTorch, and ONNX right out of the box. Also, it handles batching and scaling well, which the other options don’t focus on. A and C are more about deployment environments and pipelines, not multi-framework serving, so that rules them out quickly.
Probably D, since Triton is specifically built to serve models from different frameworks all in one place without extra hassle. The other options focus more on optimization or deployment setups, not multi-framework serving.
Not B, TensorRT optimizes models but doesn’t serve multiple frameworks directly.
D makes the most sense here since Triton supports multiple frameworks like TF, PyTorch, and ONNX for serving models efficiently.