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esafak • today at 1:15 PM • 2 replies • view on HN

Has anyone calculated the effective intelligence of these quantized models?

I think publishing benchmarks with quantized models should become standard practice.


Replies

nsagent • today at 1:54 PM

See this recent paper: Quantization Degradation in Large Language Models: A Signal–Noise Perspective [1].

  We observe that such degradation varies substantially across these factors: 4-bit quantization usually preserves performance, 2-bit often causes broad degradation
This repo uses 2-bit quantization and removes some of the experts for its smallest fastest model. Make of that what you will.

[1]: https://arxiv.org/abs/2608.08188

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mkl • today at 1:23 PM

There's some info in the README, including:

> Coder: a coding version with half of the experts removed. It reaches 91% of the full model's SWE-bench Verified score (measured by its authors) and fits 32 GB of RAM.

https://github.com/Niko1221/Strata#which-model-should-i-pick

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