Huawei Cloud introduces Pangu Models 5.5

Zhang Ping'an, Executive Director of Huawei, CEO of Huawei Cloud, unveiled Pangu Models 5.5 during his HDC 2025 keynote, featuring significant upgrades across five capabilities: natural language processing (NLP), computer vision (CV), multi-modal, prediction, and scientific computing. Mr. Zhang also showcased Pangu Models' transformative applications in the agriculture, manufacturing, and scientific research sectors.

Huawei Cloud's Pangu Models focus on industry-facing applications. Pangu Models help customers tackle the most challenging issues in their specific scenarios and reimagine both operations and efficiency across numerous industries. Pangu Models 5.5 have been fully upgraded to deliver new value for industries.

Huawei Cloud announces Pangu Models 5.5

Pangu Natural Language Processing (NLP) Model: The new 718B deep thinking model is a MoE model consisting of 256 experts. It has been drastically enhanced in knowledge reasoning, tool invoking, and mathematics, and it is among the industry's top-ranking models.

Pangu Models 5.5 have been upgraded to improve user experience in long-sequence processing, low hallucinations, integrated fast and slow thinking, and agents. For example, Pangu enables the technology of adaptive fast and slow thinking integration. By building difficulty-aware fast and slow thinking data and adopting two-phased progressive training, the model can adaptively switch between fast and slow thinking based on the difficulty of problems. In this way, the model can provide agile replies to simple problems and perform deep thinking on complex problems, improving the overall model inference efficiency by eight times.

The Pangu DeepDiver uses key technologies such as long-chain problem synthesis and progressive rewards to achieve highly efficient execution in web page search and common Q&A. For example, DeepDiver can complete a more than 10-step complex Q&A within 5 minutes, and generate professional survey reports of over 10,000 words, greatly improving work efficiency for users.

Pangu Models aim to help industry customers build their own models without "reinventing the wheel". Huawei Cloud provides enterprises with six core capabilities: Pangu foundation and industry-specific models, pre-training and post-training corpus, data engineering tool sets, model training tool sets, industry-specific judge models, and industry-specific evaluation platforms. With Huawei Cloud ModelArts, enterprises can perform high-quality training, fine-tuning, and reinforcement learning on their accumulated data assets, in this way quickly building their own professional models.

The Chinese Academy of Agricultural Sciences (CAAS) has trained Pangu foundation models using large volumes of professional literature and cross-species multi-omics data in order to build its own Agricultural Scientific Discovery Model focused on scientific crop breeding. This model implements precise agricultural knowledge Q&A, efficient genetic analysis, and targeted site design to shorten the early R&D cycle and help researchers more accurately improve the target traits of crops. The CAAS team has already been successful in improving a rice strain based on the intelligent agricultural research system enabled by the Agricultural Scientific Discovery Model. This has led to the plant height being reduced by around 25% compared with conventional rice strains, while significantly improving lodging resistance and maintaining the same yield.

At the conference, Zhang Ping'an 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 realizes 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 generalization capabilities for predictions across different industries and scenarios.

Conch Cement uses the Pangu Model to predict the 3-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.