kingjones777/Qwen3.5-27B-ROCmFP4-GGUF overview
Qwen3.5 27B — ROCmFP4 / ROCmFPX GGUF First ROCmFP4/ROCmFPX quantization of Qwen/Qwen3.5 27B . Four quants, built from the Hub BF16 GGUF no re conversion , each…
Runs locally from ~888.0 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| Qwen3.5-27B-Q4_0_ROCMFP4_COHERENT.gguf | GGUF | Q4_0_ROCMFP4_COHERENT | 14.72 GB | Download |
| Qwen3.5-27B-Q6_0_ROCMFPX_AGENT.gguf | GGUF | Q6_0_ROCMFPX_AGENT | 23.22 GB | Download |
| Qwen3.5-27B-Q8_0_ROCMFPX.gguf | GGUF | Q8_0_ROCMFPX | 25.92 GB | Download |
| Qwen3.5-27B-Q8_0_ROCMFPX_AGENT.gguf | GGUF | Q8_0_ROCMFPX_AGENT | 26.28 GB | Download |
| mmproj-BF16.gguf | GGUF | BF16 | 888.0 MB | Download |
Model Details
| Model ID | kingjones777/Qwen3.5-27B-ROCmFP4-GGUF |
|---|---|
| Author | kingjones777 |
| Pipeline | image-text-to-text |
| License | apache-2.0 |
| Base model | Qwen/Qwen3.5-27B |
| Last modified | 2026-08-17T19:02:33.000Z |
Model README
---
license: apache-2.0
base_model: Qwen/Qwen3.5-27B
base_model_relation: quantized
pipeline_tag: image-text-to-text
library_name: gguf
tags: [gguf, rocmfp4, rocmfpx, strix-halo, gfx1151, amd, rocm, qwen, multimodal, quantized]
---
Qwen3.5-27B — ROCmFP4 / ROCmFPX GGUF
First ROCmFP4/ROCmFPX quantization of Qwen/Qwen3.5-27B. Four quants, built from the Hub
BF16 GGUF (no re-conversion), each individually verified on real hardware.
Built for AMD Strix Halo (gfx1151) — Ryzen AI MAX+ 395, 128 GB unified — with the
ROCmFPX llama.cpp fork.
> ⚠️ Needs a ROCmFPX-capable llama.cpp build. These will not load in stock
> llama.cpp / Ollama / LM Studio.
Variants
| file | ftype | size | token_embd | decode | correctness |
|---|---|---|---|---|---|
| Qwen3.5-27B-Q4_0_ROCMFP4_COHERENT.gguf | 102 | 14.72 GiB | Q6_K | 12.08 t/s | 3/3 |
| Qwen3.5-27B-Q6_0_ROCMFPX_AGENT.gguf | 114 | 23.22 GiB | Q8_0 | 7.11 t/s | 3/3 |
| Qwen3.5-27B-Q8_0_ROCMFPX.gguf | 111 | 25.92 GiB | Q8_0 | 7.17 t/s | 3/3 |
| Qwen3.5-27B-Q8_0_ROCMFPX_AGENT.gguf | 115 | 26.28 GiB | Q8_0 | 7.22 t/s | 3/3 |
mmproj-BF16.gguf is included — required for image input (-fa off).
Which to pick: the 4-bit (102) — fastest and smallest, same answers as the 8-bits.
⚠️ Q6_0_ROCMFPX_AGENT (114) is the weakest choice here: larger than the 4-bit and
slower than the plain 8-bit. The AGENT recipe raises speculative-draft acceptance, and
Qwen3.5-27B ships no drafter, so that benefit cannot apply. It is included for completeness.
Measured — not estimated
Hardware: Ryzen AI MAX+ 395 (Strix Halo, gfx1151), 128 GB unified.
-ngl 999 -c 4096 -fa on -fit off. 300 tokens, warm-up discarded, median of 3.
| ftype | run 1 / 2 / 3 | median | spread |
|---|---|---|---|
| 102 | 12.09 12.04 12.08 | 12.08 | 1.004 |
| 114 | 7.06 7.11 7.11 | 7.11 | 1.007 |
| 111 | 7.11 7.17 7.17 | 7.17 | 1.008 |
| 115 | 7.13 7.22 7.24 | 7.22 | 1.015 |
No MTP/EAGLE drafter ships with this model, so these are the deployed numbers with
nothing left on the table.
Speculative decoding
Qwen ships no official MTP/draft head for Qwen3.5-27B — verified against the base repo file list
and config.json (unlike Qwen3.8-27B, which does). The decode figures above are therefore
no-speculation numbers.
⭐ However, classic draft-model speculation should work, because every Qwen3.5 model shares the
same vocabulary (248320) and architecture (qwen35):
llama-server -m Qwen3.5-27B-Q4_0_ROCMFP4_COHERENT.gguf \
--spec-type draft-simple --model-draft Qwen3.5-0.8B-Q4_0_ROCMFP4_COHERENT.gguf \
--spec-draft-ngl 99 --spec-draft-n-max 3 -ngl 999 -c 4096 -fa on -fit off
⚠️ We have not measured this — the box was needed elsewhere before the test completed. It is
offered as a documented, plausible route, not a benchmarked claim. If you try it, the levers that
mattered on comparable models were --spec-draft-n-max (sweep 2–5) and using the smallest
drafter that still accepts well.
Third-party heads exist (VirVen/Qwen3.5-27B-EAGLE3-v2, selimaktas/Flow-Drafter-Qwen3.5-27B) but
are SGLang-specific or research artifacts and do not load in llama.cpp.
Head protection
Qwen3.5-27B does not tie embeddings — it has a real output.weight, and both it and
token_embd are protected (Q6_K on the 4-bit, Q8_0 on the rest). Audited by exact
tensor name. Note the smaller Qwen3.5 models do tie, so the same flags behave
differently across this family — pass both.
15804651168 Qwen3.5-27B-Q4_0_ROCMFP4_COHERENT.gguf
24936068768 Qwen3.5-27B-Q6_0_ROCMFPX_AGENT.gguf
27834807968 Qwen3.5-27B-Q8_0_ROCMFPX.gguf
28214425248 Qwen3.5-27B-Q8_0_ROCMFPX_AGENT.gguf
Credits
- Base model: Qwen/Qwen3.5-27B
- Quantization stack: ROCmFPX
Run kingjones777/Qwen3.5-27B-ROCmFP4-GGUF with guIDE
Download guIDE — the AI-native code editor with local LLM inference and 69 built-in tools.
Source: Hugging Face · Compare models