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KissMyShinyArse/Qwen3.8-27B-GGUF
Qwen3.8-27B-GGUF is a machine learning model from KissMyShinyArse. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
UPDATE: Q5CR, Q6CR and Q8CR have been added to https://github.com/TheTom/llama-cpp-turboquant
Downloads · 30 days
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.gguf31.5 GB · 100%
From the Hugging Face model README
UPDATE: Q5_CR, Q6_CR and Q8_CR have been added to https://github.com/TheTom/llama-cpp-turboquant
This quant is based on Unsloth's UD-Q8_K_XL quant, with the Q8 weights swapped for Q8_CR (ConvRot).
⚠️ Proof of concept - CUDA only.
| Quant | Size (GiB) | PPL (Q) | PPL Ratio | ΔPPL | Mean KLD | RMS Δp (%) | Same Top-p (%) |
|---|---|---|---|---|---|---|---|
| UD-Q8_K_XL-Q8_to_Q8_CR (this one) | 29.30 | 6.9565 | 1.00089 | 0.0062 | 0.00037 | 0.587 | 99.263 |
| Q8_CR | 27.05 | 6.9585 | 1.00118 | 0.0082 | 0.00043 | 0.598 | 99.099 |
| UD-Q8_K_XL (Unsloth, baseline) | 29.30 | 6.9537 | 1.00049 | 0.0034 | 0.00083 | 0.823 | 98.992 |
| Q8_0 | 27.05 | 6.9560 | 1.00082 | 0.0057 | 0.00095 | 0.942 | 98.742 |
Build llama.cpp with the patch from this repo:
git clone https://github.com/ggml-org/llama.cpp
cd llama.cpp
git checkout 749f688fcaa4c472ec034b08cb8a907c45cfaa02
patch -Np1 < /path/to/q8_cr.patch
cmake -B build -DBUILD_SHARED_LIBS=OFF -DGGML_CUDA=ON .
cmake --build build --config Release
This quantization is CUDA-only: inference requires an NVIDIA GPU. On a system
without CUDA, model loading fails with failed to find a compatible buffer type. For full speed, offload all layers to the GPU (-ngl 99). Partial
offload works, but every rotated matmul still executes on the GPU (activations
and weights are copied per layer), so generation becomes extremely slow.
Quantize the BF16 GGUFs using the patched llama-quantize:
llama-quantize Qwen3.8-27B-BF16-00001-of-00002.gguf Qwen3.8-27B_Q8_CR.gguf Q8_CR
See RESEARCH.md.