Sakana AI releases 100 billion parameter hybrid expert model Namazu and deploys it on the Modal platform
Sakana AI has released Namazu, a hybrid expert model with 1 trillion parameters, for Japanese business contexts, web search, and code execution. The Modal team achieved memory and throughput improvements for Namazu on the Modal platform through NVFP4 precision quantization, custom DFlash model training, and kernel-level optimization, and it supports real-time training of 3 billion tokens. After deployment, the model's inference speed increased by 40%, the acceptance rate improved by 43%, and the latency decreased by 52%.






















