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Huawei Cloud ModelArts · major
ModelArts Notebook integrates multiple AI assistants and Skills
On August 13, 2026, ModelArts introduced best practices for integrating AI coding assistants like OpenClaw and Cline into Notebook.
Huawei Pangu · major
ModelArts Studio Integrates DeepSeek R1/V3 and Offers Agent Development Capabilities
ModelArts Studio serves as a unified enterprise portal delivering inference services for Huawei's Pangu models alongside third-party offerings, including the full DeepSeek R1 and V3 series. The platform also provides integrated large model services spanning data engineering, model development, domain applications, and Agent creation.
Huawei Cloud ModelArts · major
Huawei Cloud ModelArts Inference Service Upgrades: Multi-Level Flow Control, Agentic RL, and Multi-P/Multi-D Deployment
ModelArts' inference service has been upgraded with a decoupled architecture supporting gray releases and traffic mirroring for smooth rollouts, alongside multi-level flow control and rapid recovery mechanisms. An integrated evolutionary reinforcement learning framework (Agentic RL) enables continuous agent evolution, while new multi-pod/multi-device deployment modes and topology visualization improve efficiency and operational visibility. These enhancements collectively strengthen SLA guarantees and developer experience for enterprise workloads.
Huawei Cloud ModelArts · major
ModelArts Supports Trillion-Parameter, Petabyte-Scale Distributed Training Within Single Jobs
ModelArts can execute ultra-large-scale distributed tasks, supporting training for trillion-parameter models and hundred-petabyte data volumes within a single job. The platform includes built-in operations capabilities such as performance profiling and automated fault diagnosis.
Huawei Cloud ModelArts · major
Huawei Cloud ModelArts Launches Industry-First One-Click Deployment of Ascend-Adapted DeepSeek-V4-Flash
Huawei Cloud ModelArts introduces the industry's first natively adapted DeepSeek-V4-Flash model for Ascend hardware, supporting 1 million token context inference with TPOT optimized to 20ms and significantly increased single-card throughput compared to DeepSeek-V3.2.
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