An Empirical Study of openPangu Quantization on Ascend NPUs
openPangu models are attractive targets for private and domestic large-language-model deployment, yet their robustness under aggressive post-training quantization on Ascend NPUs has not been systematically characterized. This paper conducts a controlled empirical study of openPangu 1B and 7B models on Huawei Ascend 910B1 NPUs. We evaluate representative weight-only and weight-activation post-training quantization methods, including RTN, GPTQ, AWQ, SmoothQuant, GPTAQ, BiLLM, and SliM-LLM, under a unified calibration and evaluation protocol. Across 18 evaluation tasks, we find that 8-bit weight-only quantization is effectively lossless for both models, while 4-bit quantization remains pract...
| Authors | Tong Shi, Jiacheng Wang, Hui Xie et al. |
|---|---|
| Primary category | cs.LG |
| Published | 19 June 2026 |
| Last updated at source | 7 August 2026 |
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