[jono_irwin]

Yeah that’s fair. For weights specifically there often isn’t a huge dedupe win across versions since retraining tends to change most of them. That said, we generally don’t advocate including model weights in container images anyway. The main benefit for us is avoiding the need to pull the full image up front and only fetching the data actually touched during startup. On the latency side, reads happen over a local network with caching and prefetching, so the impact on request latency is typically minimal.