You can train large models with 50% less GPU memory by using better compression for optimizer states—no quality loss, drop-in replacement.
FlashOptim cuts the memory needed to train large AI models in half by storing optimizer information more efficiently. It uses smarter compression techniques for gradients and optimizer states without hurting model quality, making it possible to train 7B+ parameter models on consumer GPUs.