Quantize and Distill for Cheaper Inference
Shrink models while keeping quality high.
Shrink the Model, Not the Bill
A smaller model needs less memory and cheaper hardware to serve. Model compression trims size and cost while keeping most of the accuracy you worked for.
What Quantization Means
Quantization stores weights in fewer bits, like int8 instead of float32. The model gets roughly four times smaller and often runs faster on the same chip.
All lessons in this course
- Right-Size Instances and Replicas
- Quantize and Distill for Cheaper Inference
- Use Spot Instances for Training
- Track Cost per Prediction