Tether releases a cross-platform BitNet LoRA framework, supporting consumer-grade GPUs and large model training and inference on smartphones

Tether CEO Paolo Ardoino revealed that the Tether AI team has released a new version of QVAC Fabric, which integrates the cross-platform BitNet LoRA framework, enabling the training and inference of billion-parameter large models on consumer-grade GPUs and smartphones.

The new version of QVAC Fabric LLM has achieved cross-platform operation of BitNet LoRA fine-tuning and inference on AMD, Intel, Apple Metal, and mobile GPUs for the first time. On flagship devices, GPU inference speed is improved by 2 to 11 times compared to CPU, and memory usage is reduced by up to 90% compared to full precision models. The Tether team has completed fine-tuning of models with up to 3.8 billion parameters on flagship smartphones such as Pixel 9, S25, and iPhone 16, and has achieved fine-tuning of models with up to 13 billion parameters on the iPhone 16. The related code has been open-sourced to GitHub.