Your question is Model Quantization Tradeoffs. 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).
Explain the different kinds of model quantization and the tradeoffs.
Discuss dynamic quantization, static post-training quantization, quantization-aware training, and lower-bit formats such as INT8, INT4, and binary weights. Provide a practical implementation that compares model size, inference latency, and predictive quality before selecting a deployment strategy.