nishantsunuwar/MoCE

This is a zero-star, inactive repository (2828 days old, no recent velocity) implementing a specific variant of mixture-of-experts (MoE) architectures. While MoCE represents a refinement over standard MoE approaches—clustering experts to improve routing efficiency—the core idea is an incremental improvement on well-established MoE patterns (Transformers, Switch Transformers, Expert Choice routing). The README indicates this is likely a research implementation or academic exercise rather than a production system. No evidence of adoption, community, or ecosystem. The project appears abandoned with no forks, stars, or activity. Frontier labs (OpenAI, Anthropic, Google) have already integrated advanced MoE variants into their scaling infrastructure (GPT-4, Claude, PaLM), making this specific routing mechanism trivially implementable as a feature within their existing frameworks. The defensibility score reflects that this is a tutorial-grade research prototype with no users, no novelty beyond prior work (MoE is standard), and direct competition from well-resourced incumbents. Frontier risk is high because MoE scaling and routing optimization are core to LLM development—this specific contribution adds marginal value over existing approaches that labs already deploy.