Part of the QVAC platform, the framework can use non-Nvidia hardware, expanding support beyond the dominant GPUs typically used for AI training.
Tether, issuer of the world’s largest stablecoin by market cap, USDT, has released a new AI training framework that it says allows large language models to be fine-tuned on consumer hardware, including smartphones and non-Nvidia GPUs.
According to Tuesday’s announcement, the system, part of its QVAC platform, uses Microsoft’s BitNet architecture and LoRA techniques to reduce memory and compute requirements, potentially lowering the cost and hardware barriers to developing AI models.
The framework supports cross-platform training and inference across a range of chips, including AMD, Intel and Apple Silicon, as well as mobile GPUs from Qualcomm and Apple.
