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Chungulus/Qwen3.8-27B-GGUF
Qwen3.8-27B-GGUF is a image-text-to-text model from Chungulus. Use it for the image-text-to-text 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.
This is a vanilla quantization of Qwen/Qwen3.8-27B. It is not a fine-tune, merge, ablation, alignment change, or chat-template modification. The source weights are pinned to commit 1d4bf0f2ff6012fd82039f2fa52739d0dd7c…
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.gguf206 GB · 100%
From the Hugging Face model README
This is a vanilla quantization of Qwen/Qwen3.8-27B. It is not a fine-tune,
merge, ablation, alignment change, or chat-template modification. The source
weights are pinned to commit 1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0.
The official checkpoint uses Qwen3_5ForConditionalGeneration / qwen3_5 as
its internal architecture identifier. That string does not mean these
weights came from a Qwen3.5 model.
{
"algorithm": "llama.cpp stable K-quants and IQ quants from one F16 GGUF",
"bit_width": [
2,
3,
4,
5,
6,
8
],
"group_size": "format_defined",
"calibration_source": "none for K-quants; local representative prompts for IQ variants if required"
}
llama.cpp / 5f754ea0e2fd21e1213db7ebebfd65d938d9d69c.Calibration source: none for K-quants; local representative prompts for IQ variants if required.
sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2 at
e8f8c211226b894fcb81acc59f3b34ba3efd5f42
as a measured proxy, not as ground-truth accuracy.{
"release_gate": "PASS",
"text": [
true,
true,
true,
true,
true,
true,
true,
true,
true,
true
],
"tools": [
true,
true,
true,
true,
true
],
"vision": [
true,
true,
true
],
"mtp": {
"passed": true,
"acceleration_claimed": false,
"retention_gate": "GGUF tensor and nextn metadata inspection",
"advertise_acceleration": false
},
"bf16_source_comparison": {
"passed": true,
"mean_semantic_similarity": 0.9082151889801026,
"exact_matches": 5,
"measurements": {
"average_generation_tps": 8.600119274947904,
"peak_memory_gb": null,
"artifact_bytes": 206294771716,
"maximum_prompt_tokens_tested": 73,
"loop_rate": 0.0
},
"evaluator": {
"repo_id": "sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2",
"revision": "e8f8c211226b894fcb81acc59f3b34ba3efd5f42",
"pooling": "attention-mask mean pooling followed by L2 normalization",
"maximum_tokens": 256
}
},
"bf16_fixed_logit_comparison": "not applicable to the original 30-slot matrix"
}
No acceleration is advertised unless the MTP report contains a measured throughput improvement. Exact measurements are artifact-, prompt-, context-, and hardware-specific.
git clone https://github.com/ggml-org/llama.cpp && cd llama.cpp
git checkout 5f754ea0e2fd21e1213db7ebebfd65d938d9d69c
cmake -S . -B build -DGGML_METAL=ON -DCMAKE_BUILD_TYPE=Release
cmake --build build --config Release -j
hf download Chungulus/Qwen3.8-27B-GGUF --local-dir ../qwen38-gguf
cd ../qwen38-gguf
../llama.cpp/build/bin/llama-mtmd-cli -m ./Qwen3.8-27B-Q4_K_M.gguf --mmproj ./mmproj-Qwen3.8-27B-F16.gguf -p 'Describe the image.' --image ./image.png
Use the exact source chat-template controls for thinking (enable_thinking,
reasoning_effort, and preserve_thinking) and the native Qwen tool format.
Quantization can reduce quality, especially at very low bit widths. Runtime
support for the hybrid Gated DeltaNet/full-attention graph, vision tower,
projector, processor, and MTP component is format-specific. A loader that reads
only a language tensor is not sufficient. Tested context length and resource
measurements are recorded in validation_result.json; untested context lengths
must not be inferred from the architectural maximum.
The parent model and this unmodified quantization are distributed under the source model's Apache-2.0 license. See the official Qwen3.8-27B repository for the upstream model card and attribution.