You need to upload your time series (loss, performance metrics) to the cloud. Not your weights or models.

Reliance on cloud services is a legitimate worry though for privacy, IP, process control, reliability, etc.

The comparison between Optuna and WandB was not apples to apples. Optuna is completely self-hosted and local. It also focuses on hyperopt narrowly with flexible design unlike WandB that now assumes to be capture a large part of cloud-based MLOPS workflow.

It would be more fair to compare Optuna to Hyperopt. And I think Optuna was the better choice there, but I did simple PoCing and have no strong opinions.