costanzopadovano/Qwen3.8-27B-DFlash2-NVFP4-GGUF overview
Qwen3.8 27B DFlash2 NVFP4 GGUF This repository publishes an experimental NVFP4 GGUF conversion of the z lab/Qwen3.8 27B DFlash2 https://huggingface.co/z lab/Qw…
Runs locally from ~1.02 GB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| Qwen3.8-27B-DFlash2-NVFP4.gguf | GGUF | GGUF | 1.02 GB | Download |
Model Details
| Model ID | costanzopadovano/Qwen3.8-27B-DFlash2-NVFP4-GGUF |
|---|---|
| Author | costanzopadovano |
| Pipeline | text-generation |
| License | apache-2.0 |
| Base model | z-lab/Qwen3.8-27B-DFlash2 |
| Last modified | 2026-08-26T13:24:57.000Z |
Model README
---
license: apache-2.0
base_model:
- z-lab/Qwen3.8-27B-DFlash2
pipeline_tag: text-generation
tags:
- gguf
- qwen3.8
- nvfp4
- dflash2
- speculative-decoding
- draft-model
- llama.cpp
---
Qwen3.8-27B DFlash2 NVFP4 GGUF
This repository publishes an experimental NVFP4 GGUF conversion of the
speculative draft model. It is intended to draft for Qwen3.8-27B targets; it
is not a standalone replacement for the 27B target model.
The source weights are pinned to revision
50307d4c4cde6860d4eee73e2547cd786fe8e8a4.
The source model.safetensors SHA-256 is
67fc76d68dc5a9415511a4f394ef744d67510cd20e93b37cc2cc7d28e4bab65c;
the same payload hash is present in both public source revisions inspected on
2026-08-26.
File
| File | Bytes | SHA-256 | Tensor layout |
|---|---:|---|---|
| Qwen3.8-27B-DFlash2-NVFP4.gguf | 1,094,346,016 | 9bd8926d7d5701cee1f673dbab9e6359a739cbbfc348cb78966e8a01df8e9863 | 49 NVFP4 + 32 F32 |
The file is approximately 1.02 GiB, 46.8% smaller than the tested Q8_0 draft
and about 4.3% smaller than the tested Q4_K_M draft.
QVIR-1 R2 runtime
This artifact was validated with the experimental QVIR-1 R2 llama.cpp runtime:
- GitHub repository:
CostanzoPadovano/qwen38-nvfp4-analytical-lab
- release branch:
- immutable R2 publication commit:
07ccb1f3c80d7ab9875a5f0c402526d4644bd3b6
- R2 validation and benchmark:
qvir1_r2_qwen38_tool_trigger_fix_20260826.md
Stock llama.cpp builds may not support the DFlash2, bounded-prefill,
ngram-mod, Qwen3.8 tool-trigger, and experimental NVFP4 dispatch options used
by this profile.
Download
hf download costanzopadovano/Qwen3.8-27B-DFlash2-NVFP4-GGUF \
Qwen3.8-27B-DFlash2-NVFP4.gguf \
--local-dir qwen38-dflash2-nvfp4
The paired analytical target and vision projector are available at
costanzopadovano/Qwen3.8-27B-NVFP4-Q8-Hybrid-Analytical-GGUF.
Validated settings
The QVIR-1 R2 150K profile used:
--spec-type ngram-mod,draft-dflash
--spec-draft-n-max 4
--spec-draft-n-min 0
--spec-draft-p-min 0.55
--spec-draft-dflash-prefill-tail 16384
--spec-draft-type-k q8_0
--spec-draft-type-v q8_0
The complete, hardware-specific profile is linked above. It used a
153,600-token target context, Q8_0 target K/V cache, and two RTX 5060 Ti 16 GB
GPUs.
Measured behavior and limitations
With a Q4_K_XL target at long context, the NVFP4 draft saved approximately
0.90 GiB compared with Q8_0 while keeping long-context decode close to the Q8_0
result. The experimental Blackwell MMQ dispatcher was proven active, but the
available sample does not establish a repeatable kernel-only speedup.
With the analytical NVFP4/Q8 Hybrid target, acceptance and throughput depend
strongly on prompt content and speculative acceptance. The R2 tool-heavy
benchmark showed high sample variance. This draft should therefore be treated
as a VRAM-efficient experimental artifact, not as a guaranteed acceleration.
License and attribution
The source checkpoint is Apache-2.0. This derivative GGUF is distributed under
the same license. See NOTICE.md for upstream attribution. DFlash2, Qwen,
llama.cpp, Z-Lab, and related names remain the property of their respective
authors.
Citation
Please cite the upstream DFlash2 and DFlash work as requested by the source
authors, and cite the conversion/runtime record when using this artifact:
Costanzo Padovano. Qwen3.8-27B NVFP4 Analytical Inference Laboratory, 2026.
https://github.com/CostanzoPadovano/qwen38-nvfp4-analytical-labRun costanzopadovano/Qwen3.8-27B-DFlash2-NVFP4-GGUF with guIDE
Download guIDE — the AI-native code editor with local LLM inference and 69 built-in tools.
Source: Hugging Face · Compare models