DeltaTensors is a storage optimization tool that compresses fine-tuned model checkpoints by storing only the weight differences from a base model instead of full copies, reducing storage by ~69% on tested models while maintaining minimal performance impact. It works with existing fine-tunes post-training, supports version history through chained deltas, and enables streaming operations without loading multiple full models into memory.