QVAC Fabric's LLM solution will continue to iterate over the next few months—the goal is to enable large models to run local inference on any GPU, any operating system, and any terminal device, truly achieving large-scale deployment.

Their latest research has made a breakthrough: for the first time, they have successfully completed model fine-tuning on a mobile GPU. What does this mean? Previously, training AI models depended on cloud computing power, but now devices like smartphones and tablets can also participate. For decentralized AI networks, this could be a turning point—computing power is no longer monopolized by data centers, and everyone's device can become a network node.

The possibilities for edge computing combined with on-chain AI have expanded even further.