The Quantization Trade-off: How Low Can We Go?

[BhuvanB404]

The Quantization Trade-off: How Low Can We Go?

Context

EdgeFlow currently supports INT8 quantization.

For extreme edge environments (e.g., microcontrollers), lower-precision formats like INT4 or Binary Neural Networks (BNNs) may offer significant gains at the cost of accuracy.

Discussion Points

• Is there real demand for INT4 or BNN support?
• What accuracy loss is acceptable for edge deployments?
• How complex would backend support become?
• Should extreme quantization live behind experimental flags?

Goal

Assess whether ultra-low-precision support aligns with EdgeFlow’s mission and user base.