One row per published run: stored weight artifact bytes before and after quantization, compression ratio, observed evaluation wall-time ratio with an explicit direction label, and token throughput.
Part of the quant_eval public corpus: a per-case behavioral evaluation of full-weight and quantized large language models across eight agent-relevant task families, with paired statistical testing.
Cite this dataset: 10.5281/zenodo.22010723 —… See the full description on the dataset page:
https://huggingface.co/datasets/pbhappliedsystems/quant_eval_efficiency_and_footprint.
