  Yuan 2.0-M32, with a similar base architecture as Yuan-2.0 2B, uses a
mixture-of-experts architecture with 32 experts of which 2 experts are active.
A new router network, Attention Router, is proposed and adopted for a more
efficient selection of experts, which improves the accuracy compared to the
model with classical router network. Yuan 2.0-M32 is trained with 2000B tokens
from scratch, and the training computation consumption is only 9.25% of a dense
model at the same parameter scale. Yuan 2.0-M32 demonstrates competitive
capability on coding, math, and various domains of expertise, with only 3.7B
active parameters of 40B in total, and 7.4 GFlops forward computation per
token, both of which are only 1/19 of Llama3-70B. Yuan 2.0-M32 surpass
Llama3-70B on MATH and ARC-Challenge benchmark, with accuracy of 55.89 and 95.8
respectively. The models and source codes of Yuan 2.0-M32 are released at
Github1.
