Same INT8 Model Shows 93% to 71% Accuracy Variance Across Snapdragon Chipsets

A detailed accuracy testing study across five Snapdragon SoCs reveals critical findings: the same INT8 quantized model and ONNX export produce dramatically different results depending on the target chipset, ranging from 91.8% on Snapdragon 8 Gen 3 down to 71% on older variants. This variance occurs despite identical model weights and quantization scheme.

For practitioners deploying LLMs to mobile and edge devices, this is a sobering reminder that quantization alone doesn't guarantee consistency across hardware targets. The variance likely stems from differences in integer arithmetic implementations, memory bandwidth constraints, and hardware-specific optimizations on different generations of SoCs. This necessitates rigorous per-device testing before production deployment.

The findings underscore the importance of comprehensive hardware validation in local deployment strategies, particularly for mobile inference where device heterogeneity is inevitable. Teams must establish quality assurance workflows that test against target device families rather than assuming behavior will remain consistent across similar hardware generations.

Source: r/LocalLLaMA · Relevance: 8/10