harsh-raj-singh/CMOE

This project is a pedagogical implementation of well-documented Mixture of Experts (MoE) techniques. With 1 star and no forks, it currently functions as a personal learning experiment rather than a production tool. The MoE space is heavily dominated by large-scale research labs and infrastructure providers; high-performance implementations like MegaBlocks (used by Databricks/MosaicML), DeepSpeed-MoE (Microsoft), and Tutel provide the optimized CUDA kernels necessary for MoE to be computationally viable at scale. This project lacks the distributed training primitives or hardware-level optimizations required to compete with existing frameworks. It is highly susceptible to displacement as frontier labs continue to release more efficient, standardized MoE architectures and training recipes.