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Stop Killing Your Battery: The Ultimate Guide to Android Edge AI Quantization (INT8 vs. FP16)
If you have ever tried to run a massive Large Language Model (LLM) or a high-resolution computer vision model directly on a mobile device, you’ve likely encountered the "Thermal Wall." Your device gets hot, the frame rate drops, and the battery percentage plummets faster than a falling stone.
This isn't just bad code; it is a battle against the fundamental laws of physics.
When we deploy models like Gemini Nano to an Android device, we aren't just executing logic; we are moving massive te...
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