According to Tether’s AI research team, the company today launched QVAC MedPsy series medical language models designed for local deployment on smartphones and wearables without cloud dependency. The 1.7B-parameter version scored 62.62 on seven medical benchmarks, exceeding Google MedGemma-4B by 11.42 points and surpassing MedGemma-27B (16 times larger) on clinical scenarios like HealthBench Hard. The 4B-parameter version achieved 70.54, with 3.2x lower token consumption during inference. Released in GGUF format at approximately 1.2GB, the models enable on-device medical data processing, reducing latency, costs, and privacy risks.
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