During June 2025, G. Saichai contributed to the quic/aimet repository by enhancing ONNX quantization workflows and addressing a critical bias and weight quantizer alignment issue. Saichai introduced an allow_overwrite parameter to the ONNX simulation’s encoding management, enabling safer handling of quantization encodings and reducing the risk of accidental data loss. By ensuring bias quantizer encodings consistently match weight quantizer types across various configurations, Saichai improved reliability and prevented runtime errors in quantization experiments. The work, implemented in Python and JSON, emphasized robust unit testing and model optimization, resulting in deeper test coverage and more stable production-like quantization workflows.