SpikingBrain 7B – More efficient than classic LLMs

SpikingBrain 7B combines brain-inspired mechanisms with hybrid efficient attention and MoE modules to create a more efficient large language model. Using only 2% of typical training data, it achieves performance comparable to mainstream models while delivering 100× faster processing for long sequences and 69% sparsity at the micro level. The architecture provides valuable guidance for neuromorphic chip design and supports flexible deployment across multiple platforms.