Guan Cha Zhe Wang·2026-01-28 03:45Core Insights - The article discusses the emergence of domestic alternatives to NVIDIA's dominance in humanoid robot "brain" chip modules, highlighting the launch of the "Tongyang" series by domestic GPU company TianShu ZhiXin [1][10]. Group 1: Product Features - The Tongyang series is compatible with the CUDA ecosystem, allowing seamless switching between TianShu ZhiXin's products and NVIDIA's Orin series, thus providing more options for industrial applications in embodied intelligence [3][10]. - The Tongyang series includes four products with distinct features: - Tongyang TY1000, a compact module with industry-level computing power [3]. - Tongyang TY1100, which integrates an ARM v9 12-core CPU and a self-developed GPU module [3]. - Tongyang TY1100_NX, known for its larger memory and cost-effectiveness [3]. - Tongyang TY1200, offering up to 300 TOPS performance, aimed at advanced applications like AIPC and embodied intelligence [4][6]. Group 2: Performance Comparison - The Tongyang series boasts measured dense computing power ranging from 100 TOPS to 300 TOPS, surpassing the capabilities of NVIDIA's Orin series [4][6]. - In practical tests across various scenarios, the performance of Tongyang TY1000 has been reported to exceed that of NVIDIA's AGX Orin [4][6]. Group 3: Market Context - The year 2025 is projected to be a pivotal year for humanoid robot mass production, with IDC estimating global shipments to reach approximately 18,000 units, over 60% of which will come from Chinese manufacturers [6]. - Despite advancements, there remains a significant gap in AI computing power for humanoid robots, with Intel and NVIDIA still holding a dominant position in the market [7][8]. Group 4: Competitive Landscape - The article notes that while domestic alternatives like the RK3588 chip from Rockchip have made progress in the "small brain" segment, they fall short in AI computing power, with a maximum of 6 TOPS [7][8]. - The article highlights the potential of the Diguo Robot's new generation chip, which can achieve 560 TOPS, indicating a move towards more competitive domestic solutions [8]. Group 5: Migration and Cost Considerations - TianShu ZhiXin's adherence to the GPGPU route and compatibility with the CUDA ecosystem positions its products as a more convenient option for migration compared to other domestic alternatives [10]. - The high migration costs associated with transitioning algorithms from NVIDIA's platform to other architectures could significantly impact the development speed of domestic companies [10].