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Free8 Oct 2026 · 1 min read

Native AWQ saved idle memory and cost speech time

This follow-up separates native AutoRound AWQ from the earlier rejected emulations. It measures whether reduced residency also improves the speech request.

⚡ RTX 3060

Test the native route separately

This follow-up separates native AutoRound AWQ from the earlier rejected emulations. It measures whether reduced residency also improves the speech request.

English Turbo RTF increased from 0.446 to 0.564. Regular English G64 changed from 0.888 to 1.221; Multilingual v2 from 1.014 to 1.344; the Spanish fine-tuned candidate from 0.416 to 0.543. Lower RTF is better, so these were regressions despite the idle-memory savings.

Intelligibility did not move uniformly

For supported Spanish Multilingual v2, RTF changed from 1.018 to 1.322 while local ASR edits fell from two to zero out of fifty words. That small observation does not establish quality parity over future sentences.

An original-FP32 default-voice study is retained as a separate cohort. Different voice conditioning, warm-up counts and model families should not be mixed into one ranking.

The choice

Use native AWQ when its specific memory saving justifies the measured latency cost and the intended language passes its own checks. Neither the smaller file nor a successful API response replaces listening and output validation.

Evidence and publication boundary

This is an edited account of the recorded experiment. The linked archive is private; the methods, aggregate findings and limits are included above. Reference recordings, raw conversations, authentication material and workstation configuration are excluded.

Source: chatterbox/autoround-awq-rtx3060-2026-10-08/README.md

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