axiomofmind/Qwen3.6-35B-A3B-NVFP4-W4A16-MoE-MLP-GGUF overview
Qwen3.6 35B A3B Selective NVFP4 MoE MLP GGUF An accuracy oriented GGUF conversion of Qwen/Qwen3.6 35B A3B https://huggingface.co/Qwen/Qwen3.6 35B A3B for NVIDI…
Runs locally from ~746.6 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
Model Details
| Model ID | axiomofmind/Qwen3.6-35B-A3B-NVFP4-W4A16-MoE-MLP-GGUF |
|---|---|
| Author | axiomofmind |
| Pipeline | image-text-to-text |
| License | apache-2.0 |
| Base model | Qwen/Qwen3.6-35B-A3B |
| Last modified | 2026-08-23T14:08:36.000Z |
Model README
---
base_model:
- Qwen/Qwen3.6-35B-A3B
base_model_relation: quantized
license: apache-2.0
pipeline_tag: image-text-to-text
tags:
- gguf
- llama.cpp
- qwen3.6
- moe
- nvfp4
- modelopt
- multimodal
- mtp
- dflash
- speculative-decoding
---
Qwen3.6-35B-A3B Selective NVFP4 MoE-MLP GGUF
An accuracy-oriented GGUF conversion of Qwen/Qwen3.6-35B-A3B for NVIDIA Blackwell GPUs. Only the routed and shared-expert MLP weights use NVFP4 W4A16; attention, embeddings, the output head, vision components, and embedded MTP remain at BF16/F32 precision.
Files
| File | Purpose | Size |
| --- | --- | ---: |
| Qwen3.6-35B-A3B-NVFP4-W4A16-MoE-MLP-BF16attn-BF16head-MTP.gguf | Main model with embedded MTP | 24.58 GB |
| mmproj-Qwen3.6-35B-A3B-BF16.gguf | BF16 vision projector | 0.90 GB |
| Qwen3.6-35B-A3B-DFlash-BF16.gguf | Optional original DFlash speculative drafter | 0.78 GB |
The main GGUF works by itself for text. Add mmproj for image input. The DFlash GGUF is not a standalone model and is used instead of embedded MTP when DFlash speculation is enabled.
Precision layout
| Component | Precision |
| --- | --- |
| Routed/shared-expert gate, up, and down weights | NVFP4 W4A16 |
| Full and linear attention | BF16/F32 |
| Embeddings, routers, and lm_head | BF16/F32 |
| Vision and MTP/NextN | BF16/F32 |
The main GGUF contains 240 NVFP4 tensors and retains all other tensors at source precision.
Usage
A recent CUDA build of llama.cpp with Qwen3.6 NVFP4 support is required. DFlash additionally requires a compatible build such as DFlash 2 PR #27342.
Embedded MTP:
llama-server \
-m Qwen3.6-35B-A3B-NVFP4-W4A16-MoE-MLP-BF16attn-BF16head-MTP.gguf \
--mmproj mmproj-Qwen3.6-35B-A3B-BF16.gguf \
--ctx-size 32768 --flash-attn on --n-gpu-layers -1 \
--cache-type-k q8_0 --cache-type-v q8_0 \
--spec-type draft-mtp --spec-draft-n-max 2
Original DFlash:
llama-server \
-m Qwen3.6-35B-A3B-NVFP4-W4A16-MoE-MLP-BF16attn-BF16head-MTP.gguf \
-md Qwen3.6-35B-A3B-DFlash-BF16.gguf \
--mmproj mmproj-Qwen3.6-35B-A3B-BF16.gguf \
--ctx-size 32768 --flash-attn on --n-gpu-layers -1 \
--cache-type-k q8_0 --cache-type-v q8_0 \
--spec-type draft-dflash --spec-draft-n-max 7 --spec-draft-ngl all \
--cache-type-k-draft q8_0 --cache-type-v-draft q8_0
Remove --mmproj for text-only use.
Validation
- Structural audits passed: 240 intended MoE tensors in NVFP4; attention,
lm_head, vision, and MTP retained at BF16/F32. - The target and projector successfully allocated a 262,144-token context and completed a real image request. A near-limit prompt has not yet been tested.
- DFlash completed correctness and code-generation smoke tests at 32,768 context. The longer test accepted 210 of 308 drafted tokens (68.18%) and generated at 330.61 tok/s on one RTX PRO 6000 Blackwell; this is not a controlled benchmark.
Sources and license
- Target: Qwen/Qwen3.6-35B-A3B
- Draft: z-lab/Qwen3.6-35B-A3B-DFlash
- Quantization: NVIDIA Model Optimizer
- Runtime and conversion: ggml-org/llama.cpp
The source target and DFlash checkpoints are released under Apache-2.0.
Run axiomofmind/Qwen3.6-35B-A3B-NVFP4-W4A16-MoE-MLP-GGUF with guIDE
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