Broken on Arrival: Silently Defective LLM Artifacts in Public Model Registries and How to Catch Them

Researchers have identified a security and reliability gap in public model registries, where quantized GGUF files are distributed to users without any functional verification. A study of 327 artifacts revealed that many of these locally deployed models contain silent defects that impair performance after conversion. This discovery highlights a lack of quality control in the open-source pipeline, as developers currently have no automated way to ensure that downloaded model weights function as intended.