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YTan2000/Qwen3.6-27B-MTP-TQ3_4S
Qwen3.6-27B-MTP-TQ3_4S is a text generation model from YTan2000. Use it when you need the model to write or continue text. It is set up for gguf. The card lists the license as apache-2.0.
Canonical artifact: Qwen3.6-27B-MTP-TQ34S
Downloads · 30 days
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.gguf14.4 GB · 100%
From the Hugging Face model README
Canonical artifact: Qwen3.6-27B-MTP-TQ3_4S
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TurboQwen3.6 is the public release name for the TurboQuant GGUF build of the Qwen3.6 27B MTP model line.
The exact file and runtime artifact name remains:
Qwen3.6-27B-MTP-TQ3_4S.ggufunsloth/Qwen3.6-27B-MTP-GGUFturbo-tan/llama.cpp-tq3This release is intended for the public TurboQuant runtime fork:
https://github.com/turbo-tan/llama.cpp-tq3It requires TQ3_4S runtime support and draft-MTP support. It is not expected to run correctly on stock llama.cpp builds that do not contain these extensions.
The multimodal projector is published separately so the main Hugging Face page stays anchored on the 27B text model:
https://huggingface.co/YTan2000/Qwen3.6-27B-MTP-TQ3_4S-mmprojQwen3.6-27B-MTP-TQ3_4S.gguf - main model, 13.39 GiBmmproj.gguf - matching multimodal projector, 0.87 GiB, hosted in the separate projector repo abovethumbnail.png - model card imagebenchmark.png - benchmark summary imageUse flash attention at runtime and enable draft-MTP speculative decoding:
./build/bin/llama-server \
-m Qwen3.6-27B-MTP-TQ3_4S.gguf \
--mmproj mmproj.gguf \
--alias Qwen3.6-27B-MTP-TQ3_4S.gguf \
--host 127.0.0.1 --port 8080 \
-c 32768 -np 1 -ngl 99 -fa on \
-ctk q8_0 -ctv tq3_0 \
--spec-type draft-mtp \
--spec-draft-n-min 1 \
--spec-draft-n-max 2 \
--spec-draft-p-min 0.0 \
--reasoning off --jinja
Important build note:
-fa on above is the runtime flash-attention flag.GGML_CUDA_FA_ALL_QUANTS.-fa on with GGML_CUDA_FA_ALL_QUANTS=OFF.For a smaller local smoke, reduce context to 4096:
./build/bin/llama-server \
-m Qwen3.6-27B-MTP-TQ3_4S.gguf \
--mmproj mmproj.gguf \
--alias Qwen3.6-27B-MTP-TQ3_4S.gguf \
--host 127.0.0.1 --port 8096 \
-c 4096 -np 1 -ngl 99 -fa on \
-ctk q8_0 -ctv tq3_0 \
--spec-type draft-mtp \
--spec-draft-n-min 1 \
--spec-draft-n-max 2 \
--spec-draft-p-min 0.0 \
--reasoning off --jinja --no-warmup
Then:
curl -s http://127.0.0.1:8096/v1/chat/completions \
-H 'Content-Type: application/json' \
-d '{"model":"Qwen3.6-27B-MTP-TQ3_4S.gguf","messages":[{"role":"user","content":"Write ONLY the word ok."}],"max_tokens":32,"temperature":0}'
Expected assistant content:
ok
Local BenchLoop comparison on RTX 3090, using draft-MTP and the runtime settings above:

| Metric | Result |
|---|---|
| Overall score | 86.28 |
| EasyCode | 100.00% |
| Hard86 | 88.4% |
| Toolcall | 96.67% |
| Data extract | 90.97% |
| Instruct follow | 76.67% |
| Reason math | 73.33% |
| Generation speed | 44.80 tok/s |
| Size | 13.39 GiB |
The packaged benchmark summary image is included in this repo as benchmark.png.
--spec-type draft-mtp with --spec-draft-n-max 2.--spec-draft-p-min 0.0 on the current TurboQuant runtime.-ctk q8_0 -ctv tq3_0 for the validated release profile.0.00000 on long prompts, stop and check the runtime build and launch flags before benchmarking.Use is subject to the base model license and the license terms of the runtime components used to run the GGUF.