True 4-Bit Quantized CNN Training on CPU – 92.34% on Cifar-10

Re:True 4-Bit Quantized CNN Training on CPU – 92.34% on Cifa... by jcalvinowens on Tuesday March 17, 2026 @03:37AM (#47409682)

> true 4-bit precision

This isn't one of the new block floating point schemes, it's bona fide 4-bit precision weights. It boggles my mind that can actually work.

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Re:True 4-Bit Quantized CNN Training on CPU – 92.34% on Cifa... by yorwba on Tuesday March 17, 2026 @08:56AM (#47412016)

Well, the weights are accumulated in full precision and are multiplied by a full-precision scale factor after quantization, and the activations and backward pass are computed in full precision as well, so it's not quite true 4-bit precision training. The resulting model can be stored with just slightly more than 4 bits per parameter, though.

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Re:True 4-Bit Quantized CNN Training on CPU – 92.34% on Cifa... by jcalvinowens on Tuesday March 17, 2026 @09:33AM (#47412436)

I really just don't understand how the quantization error doesn't ruin the results. Is there some reading you'd recommend?

I can easily understand how the block formats win.

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