Tether released the sidechain voice recognition model QVAC TranscribePsy

The stablecoin issuer Tether's Tether AI Research (referred to in the text as Tether Data, S.A. de C.V.) has released the open-source multilingual automatic speech recognition model QVAC TranscribePsy. This model has 254 million parameters and runs entirely on-device, suitable for smartphones, smart glasses, and humanoid robots, with audio not needing to be uploaded to the cloud; smart glasses can process in near real-time via Bluetooth or Wi-Fi, and the model can also run on the robot's onboard processor.

Evaluation shows that its word error rate on the Open ASR Leaderboard is 8.02%, 6.58% on Multilingual LibriSpeech, and 21.56% on Common Voice. It outperforms the specifically mentioned Qwen3-ASR-0.6B, omniASR-CTC-1B-v2, OWSM-CTC-v4, and Whisper-Medium on Multilingual LibriSpeech. Among six tested smartphones, it is the fastest model, being 2.6 times faster than the second fastest model and 5.7 times faster than Whisper-small. The Core ML version transcribes 10 minutes of audio into 1.65 seconds on the iPhone 17 Pro Max, occupying less than half the disk space of a certain tested Core ML competitor and using 1.7 times less memory.