Your question is Quantization Impact on Models. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
Describe how quantization affects model accuracy and latency in neural networks.
Discuss how converting FP32 weights and activations to INT8 or lower precision changes numerical representation, memory usage, hardware execution, and inference speed. Include the difference between post-training quantization and quantization-aware training, plus one concrete deployment example. Keep the discussion focused on inference behavior and practical trade-offs.