Author @0xSero points to the turboderp-org/exllamav3 repository (exllamav3/doc/exl3.md) and argues their optimized quantization/inference method produces good, fast 2–3 bit LLMs on consumer GPUs, claiming it achieves the lowest KLD compared with other compression methods and recommending readers follow the linked implementation.
@0xSero (2026-08-02) claims a quantization method in the exllamav3 repo (turboderp-org/exllamav3, doc/exl3.md) yields high-quality, fast 2–3 bit models for local consumer GPUs.
Read more here, I think this is how we get to good, fast 2-3 bit models. This method has the lowest kld compared to any other compression method.
github.com/turboderp-org/exl…
Link
exllamav3/doc/exl3.md at master · turboderp-org/exllamav3
An optimized quantization and inference library for running LLMs locally on modern consumer-class GPUs - turboderp-org/exllamav3
github.com