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utautako/Qwen3.6-27B-NVIDIA-NVFP4-MTP-GGUF
Qwen3.6-27B-NVIDIA-NVFP4-MTP-GGUF is a image-text-to-text model from utautako. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. It is set up for llama.cpp. The card lists the license as apache-2.0.
GGUF conversion of nvidia/Qwen3.6-27B-NVFP4, preserving NVIDIA NVFP4 tensors, with MTP speculative decoding and a BF16 vision projector. Benchmarked on an RTX 5090 with llama-benchy.
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From the Hugging Face model README
GGUF conversion of nvidia/Qwen3.6-27B-NVFP4, preserving NVIDIA NVFP4 tensors, with MTP speculative decoding and a BF16 vision projector. Benchmarked on an RTX 5090 with llama-benchy.
q/k/v/o) and the linear-attention / DeltaNet projections are quantized to Q4_K (down from the original FP8) to keep this build compact. For those layers kept at Q8_0 for better accuracy — about +3 GB — see the Q8attn variant.draft-mtp speculative decoding.mmproj file for image input.llama-benchy using MTP depth d=3.| Component | Source |
|---|---|
| Base model | Qwen/Qwen3.6-27B |
| NVFP4 source checkpoint | nvidia/Qwen3.6-27B-NVFP4 |
| Runtime target | llama.cpp |
| File | Size | Description |
|---|---|---|
Qwen3.6-27B-NVIDIA-NVFP4-MTP.gguf | 14.66 GiB / 15,747,650,944 bytes | Main GGUF. NVFP4 tensors preserved; MTP layer included. |
mmproj-Qwen3.6-27B-NVIDIA-NVFP4-BF16.gguf | ~888 MiB / 931,146,304 bytes | BF16 vision projector for image input. |
llama-server \
-m Qwen3.6-27B-NVIDIA-NVFP4-MTP.gguf \
--mmproj mmproj-Qwen3.6-27B-NVIDIA-NVFP4-BF16.gguf \
--spec-type draft-mtp \
--spec-draft-n-max 3 \
-ngl 999
For text-only use, omit --mmproj mmproj-Qwen3.6-27B-NVIDIA-NVFP4-BF16.gguf.
Measured on RTX 5090, llama-benchy 0.3.8, MTP depth d=3, 3 runs, generation-latency mode.
| Mode | Prompt / generation length | Prefill (pp) tok/s | Generation (tg) tok/s | Peak generation tok/s |
|---|---|---|---|---|
| Text-only | pp512 / tg512 | 2676.94 ± 51.88 | 112.69 ± 3.13 | 130.33 ± 7.41 |
| Text-only | pp4096 / tg512 | 3401.62 ± 94.87 | 116.38 ± 3.25 | 136.33 ± 4.50 |
| Vision + mmproj | pp512 / tg512 | 3337.94 ± 382.60 | 111.31 ± 7.18 | 126.33 ± 8.38 |
| Vision + mmproj | pp4096 / tg512 | 3650.71 ± 86.68 | 114.15 ± 3.52 | 131.00 ± 2.94 |
For reference, the no-speculative baseline measured in the same project notes was about 70.75 tok/s on pp512/tg512, so MTP d=3 gives roughly +59% generation throughput in that test.
| Field | Value |
|---|---|
| GGUF architecture | qwen35 |
| License metadata | apache-2.0 |
| Text layers | 64 |
| MTP layers | 1 |
qwen35.block_count | 65 |
qwen35.nextn_predict_layers | 1 |
| Vision projector architecture | clip / qwen3vl_merger |
| Vision projector precision | BF16/F32 |
| Tensor type | Count |
|---|---|
| NVFP4 | 193 |
| Q4_K | 279 |
| Q6_K | 34 |
| F32 | 746 |
| Total | 1252 |
The conversion keeps the original NVFP4 tensors instead of requantizing all weights to K-quants.
Attention (q/k/v/o) and the linear-attention / DeltaNet projections are quantized to Q4_K (the
original checkpoint stored them as FP8), which keeps this build compact; the remaining non-NVFP4
tensors are stored as K-quants or F32 as appropriate. If you want those attention / DeltaNet layers
at Q8_0 for better accuracy — about +3 GB — use the
Qwen3.6-27B-NVIDIA-NVFP4-MTP-Q8attn-GGUF
variant instead.
The upstream models are licensed under Apache-2.0:
This repository redistributes a GGUF format conversion of the NVIDIA NVFP4 checkpoint under the same Apache-2.0 license. Please also follow the terms and usage guidance of the upstream model cards.
Thanks to the Qwen team for the base model, NVIDIA for the NVFP4 ModelOpt checkpoint, and the llama.cpp project for GGUF, NVFP4, MTP, and multimodal runtime support.