At the recent Huawei Developer Conference 2025 (HDC 2025), Zhang Ping’an, Executive Director of Huawei, CEO of Huawei Cloud, released five Pangu industry-specific deep thinking models covering the medical, finance, government, industrial and automotive domains. These models will be officially launched in June and will accelerate intelligent transformation across industries.
Pangu Multimodal Model: Huawei Cloud released a new model – the Pangu World Model based on the Pangu Multimodal Model. The Pangu World Model generates digital physical spaces for intelligent driving and other scenarios.
For example, in intelligent driving training, after the driving scenario, driving control information and road network data of the first frame are input, the Pangu World Model can generate a driving video simulating that which is generated by a camera and a point cloud generated by lidar, along with a large amount of training data for intelligent driving, without relying on costly real road video collection. Based on the Pangu Multimodal Model, Guangzhou Automobile Group (GAC Group) works with Huawei Cloud to achieve pixel-level mapping between videos (2D modality) and point clouds (3D modality). This means corner cases in complex scenarios can be reproduced within minutes, providing strong support for efficient end-to-end model iteration with one version iterated in just two days.
Pangu Prediction Model: This model uses the industry’s first triplet transformer unified pre-training architecture, which realises unified triplet encoding of data from different industries, including table data from manufacturing-process parameters, time series data from device-running logs and image data from product inspections. The model efficiently processes and pre-trains this data within the same framework, greatly improving the accuracy of prediction and providing better generalisation capabilities for predictions across different industries and scenarios.
Conch Cement uses the Pangu Model to predict the three-day and 28-day strength of clinkers, providing scientific guidance for the preparation of raw materials. This allows Conch Cement to more flexibly reuse solid waste such as urban construction waste and industrial waste in the mixtures for raw materials, all while assuring high-quality cement. Conch Cement has thus been able to reduce costs, assist in urban waste disposal and contribute to a greener environment.
Pangu Scientific Computing Model: Huawei Cloud continuously deepens the combination of Pangu Scientific Computing Model and a wider range of scientific application fields. The Meteorological Bureau of Shenzhen Municipality further upgraded the Zhiji Model based on Pangu to implement regional weather forecasting. Such forecast results more closely reflect changes in weather systems and help the Bureau forecast weather more accurately. The Chengdu-Chongqing region in China’s Sichuan province has typically strong and intense rainfalls. In response, Chongqing Meteorological Service has built the Tianzi 12-hour Weather Forecast Model based on Pangu to enhance the capabilities of daily forecasting and warning against extreme weather. Shenzhen Energy Group uses Pangu to predict short- and mid-term wind and solar energy yields, which helps them adjust power generation more agilely to improve energy development efficiency.
Pangu CV Model: Huawei Cloud has released a 30B-parameter CV model based on the new MoE architecture. This is the largest CV model in the industry and supports multi-dimensional, pan-vision perception, analysis and decision-making. Pan-vision means that the model supports identification of images, infrared, lidar-generated point clouds, light spectrum and radar. Furthermore, the Pangu CV Model uses a cross-dimensional generation model to create a pan-vision fault sample library. This library features rare-case fault samples in industrial scenarios such as oil and gas, transportation and coal mining, greatly increasing the types of objects identified and improving the accuracy of identification in industry-specific scenarios.
CNPC has built the Kunlun Large Model based on Pangu and applied this model to more than 100 professional fields, such as exploration and development, oil refining and chemical engineering, and equipment manufacturing. In the equipment manufacturing field, the model is capable of detecting defects, such as porosity and tiny cracks in oil pipelines, with sub-millimeter precision. The model delivers about 40% higher identification efficiency and reduces manual workload by around 25%.
Over the past year, Pangu Models have been applied in more than 500 scenarios across over 30 industries. They have played a significant role in fields like government services, finance, manufacturing, healthcare, coal mining, steel, railways, autonomous driving and meteorology, helping customers reshape vertical industries.
