Researchers Release First Open-Source 1.58-Bit LLM Trained On Huawei Ascend

BitCPM-CANN just became the world’s first open-sourced 1.58-bit ternary LLM trained entirely on Chinese-developed AI infrastructure. Developed by ModelBest, Tsinghua Univ, and OpenBMB community, the entire training pipeline, from quantization operators and algorithms to the full-stack framework, was natively executed on Huawei Ascend 910B NPUs. 1.58-bit ternary weights use only 3 weight states, so the model needs far less memory when deployed on phones, PCs, cars, and local industrial devices. The harder achievement is the training system behind it: QAT, STE, low-bit operators, algorithms, framework work, and reproducible training scripts all had to hold together on Ascend 910B. When hardware costs rise, the winning model is not merely the one that scores higher in a chart, but the one that can be trained, reproduced, deployed, and improved under real constraints.