Tether's 1.7B Medical AI Model Outperforms 16x Larger Competitor Today

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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