Reports
AI-generated structured vendor updates
Alibaba Cloud Unveils Agent-Native Suite and Open-Source SAIL Stack to Rival CUDA
At WAIC 2026, Alibaba Cloud launched its Agent-Native cloud suite (AgentLoop, AgentTeams, AgentRun, TokenWorks), open-sourced the T-Head SAIL AI software stack, and unveiled the 2.4T-parameter Qwen 3.8-Max-Preview model and Zhenwu M890 supernode, marking a comprehensive push into agent-native cloud and open-source AI ecosystem.
Moonshot AI Launches Kimi K3: 2.8T Parameter Open-Source MoE Model at $3/$15
Moonshot AI unveils Kimi K3, a 2.8T parameter open-source MoE model with 896 experts (16 active), native vision, and 1M context. API pricing at $3/$15 input/output per million tokens undercuts rivals. Open weights release July 27. GPU capacity exhausted within 2 days. Arena score 1679 tops Fable 5.
Huawei Ascend 950 Supernode: Self-Developed HCCS Interconnect for Sovereign AI Compute Ecosystem
Huawei unveiled the Ascend 950 Supernode at WAIC, integrating 32 self-developed Ascend 950 AI processors with HCCS high-speed interconnect, achieving 2.5x compute density and supporting trillion-parameter model training, offering a sovereign AI compute alternative free from overseas supply chains.
Huawei Ascend 10K-Card Cluster Goes Live, UnifiedBus Protocol Pools All Resources
Huawei launched an Ascend 10,000-card AI cluster in Shaoguan, Guangdong, and showcased the Atlas 950 SuperPoD with its proprietary UnifiedBus interconnect supporting 8,192 NPUs at 16.3 PB/s. Huawei Cloud also entered the Gartner 2026 Cloud AI Infrastructure Leaders quadrant, reinforcing its push for a self-contained AI ecosystem.
Huawei Ascend 910C Trains 1.6T-Parameter MoE Model: First Full Pipeline on Domestic AI Chips
Huawei, in collaboration with research institutes, completed full-parameter post-training of DeepSeek-V4-Pro (1.6 trillion parameters, MoE) on an Ascend 910C cluster. Key metrics: stable 1,500 steps on 1,000 cards, 30% compute utilization, 14% operator efficiency gain, zero reliance on foreign GPUs. This marks the first end-to-end trillion-parameter training loop on domestic chips.