Breakthroughs of KunLun Core M300 Chip's Super Node Design in Large Model Training

Based on currently available information, the super node design of the KunLun Core M300 chip has achieved multiple important breakthroughs in the field of large model training:

• The M300 chip adopts an advanced super node design architecture, achieving efficient collaborative computing between chips by integrating multiple AI accelerator cards into a unified super node
• Supports flexible expansion from 32 to 256 super nodes (2025-2026 development path), providing scalable infrastructure support for large-scale model training [1]

• Optimized under the DeepSeek V3/R1 PD-separated inference architecture, the M300 super node design has achieved
  a 95% improvement in single-card performance
• Single-instance inference performance has been greatly improved by up to 8 times
  , which is of great significance for the inference deployment of large-scale language models [2]

• Supports efficient training of large models with hundreds of billions of parameters
• Special optimization for the Transformer architecture has been made to improve the computational efficiency and stability of model training

Indicator	Improvement	Significance
Single-card performance	+95%	Higher computing density, reducing unit computing cost
Inference performance	+8x	Supports real-time inference deployment of larger-scale models
Super node expansion	32→256	Supports full-process computing needs from R&D to production

1. Lowering the threshold for large model training
   : Providing a more cost-effective domestic AI computing solution through the super node architecture
2. Improving training efficiency
   : Optimized inter-chip communication and computing collaboration mechanisms shorten the model iteration cycle
3. Enhancing independent controllability
   : Reducing dependence on overseas high-end AI chips and ensuring computing power security

The super node design of the KunLun Core M300 represents an important technological breakthrough in China’s AI chip field, providing solid infrastructure support for the development of domestic large models.

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[1] Zhihu - “Behind Baidu’s Response to ‘KunLun Core Listing’: Traditional Business Under Pressure, Needing a New Story” (https://zhuanlan.zhihu.com/p/1981299020845572411)
[2] iyiou Data - “KunLun Core (Beijing) Technology Co., Ltd.” (https://data.iyiou.com/company/details/e72be2a18228cf57002f6df6ae59849d/profile)