Interesting approach running Kimi K3 in 29GB — curious what quantization/precision tradeoffs you had to make to get it there. I've been dealing with similar memory constraints running client-side AI models in the browser (background removal via ONNX runtime) — the tradeoff between model size and quality never really goes away, just moves where you hit it.
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