Hey guys! Today, we're releasing the highest accuracy Qwen3.8-27B GGUFs.
Our new Unsloth AI Dynamic V3.1 GGUFs lead by 5–10% on average across Terminal Bench, DeepSWE & more benchmarks. We’re working on even better version of Dynamic quants for Qwen4
Run on 12GB+ RAM setups.
To compare GSQ-RCO and Exllama-v3, we had to exclude the token embedding layer from the x axis, as Exllama-v3 uses BF16 for it. If you consider the full download size and total RAM usage for Exllama-v3, then adding the BF16 embedding table and including all embedding sizes changes the plots. Our main plots's x axis removes the embedding layer sizes from all quant providers. However on pure RAM usage and disk space usage vs accuracy, the below plot in the comments the true reflection of actual usage.
From their Reddit post.
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