Deploying physical AI on wearables and phones requires real-time perception inside…
This is a dev post classified by Jev as Other (a launch), kept by the Dev Radar because it carries real work, not commentary.
Deploying physical AI on wearables and phones requires real-time perception inside extreme thermal and battery limits. Reka EdgeQ is an optimized on-device VLM running natively on @Qualcomm #Snapdragon 8 Elite’s Hexagon NPU. ⚡️ 0.73s Time to First Token (Image) 📹 +34 pts over Gemma 4 E4B on MLVU video benchmarks 🔋 6.9 mWh energy per inference (~3x lower heat overhead) By custom-tuning our ConvNeXt V2 vision encoder and decoder directly for the #NPU, EdgeQ keeps the GPU completely idle, minimizing thermal throttling under sustained continuous load. 🔗Our technical breakdown: https://reka.
Posted by Reka (20.6k followers) 1 h ago · 3 likes · 372 views · view the original post on X. Kept by the Dev Radar as Other.
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