To store and retrieve large-scale PyTorch model states efficiently, I would use a combination of a relational database for metadata and a distributed object storage solution for the actual model weights. Using a key-value store like Redis can also speed up access times for frequently accessed models while employing batching for database writes to reduce overhead.