Tether open-sources edge-side vision-language model VisionPsy-Nano
2026.07.29 20:10:14
According to Tether’s official blog, QVAC, an AI research project under Tether Data, has open-sourced VisionPsy-Nano—a compact vision-language model built for end-device and edge deployment. With around 460 million parameters, the model brings multimodal understanding capabilities that previously required cloud infrastructure directly to mobile devices. Among all evaluated end-side vision-language models with fewer than 500 million parameters, VisionPsy-Nano scored the highest overall normalized score of 62.3, outperforming competing models from Liquid AI, Hugging Face, and others in 16 out of 17 benchmark tests. Tether is launching two versions of the model: the Flash version, optimized for low latency, which retains roughly 99% of the full model’s quality while drastically improving inference speed. Both versions are open-sourced under the Apache 2.0 license. Paolo Ardoino, CEO of Tether, noted that this proves local-first, efficient AI is a viable approach, enabling powerful and private AI to run on devices people already have.
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