---
license: apache-2.0
base_model: unsloth/Qwen3.6-27B-MTP-GGUF
base_model_relation: quantized
pipeline_tag: text-generation
library_name: llama.cpp
language:
- en
tags:
- gguf
- rocmfpx
- rocm
- amd
- strix-halo
- gfx1151
- mtp
- qwen3
- vision
---

# Qwen3.6-27B · ROCmFPX

### Stock `Q6_K` quality, ~30% faster prompt-processing on AMD Strix Halo (`gfx1151`)

ROCmFPX 3→8-bit quants of [`unsloth/Qwen3.6-27B-MTP-GGUF`](https://huggingface.co/unsloth/Qwen3.6-27B-MTP-GGUF) — the general-purpose base, with MTP speculative decoding + Qwen3-VL vision. Neutral imatrix calibration, so base behavior is preserved (not skewed toward code).

| | |
|---|---|
| **Quality** | ≈ stock `Q6_K` (PPL within error) |
| **Prompt processing** | **+29%** vs Q6_K (short ctx) → +20% at 64k — measured |
| **Decode** | \~18 tok/s with MTP (~9 raw) |
| **Vision** | Qwen3-VL — bundled `mmproj/` |

> ⚠️ **Requires the [ROCmFPX fork](https://github.com/charlie12345/ROCmFPX)** (build `main` — the FP* types are merged in) — custom AMD quant types (enum IDs 110–115), not upstream-stable. **Won't load** in stock llama.cpp / LM Studio / Ollama. HF's precision badge is wrong — **pick the file by name**.

## Pick a tier

| File suffix | Size | Best for |
|---|---|---|
| `…embF16-headQ6-Q6_0_ROCMFPX.gguf` ★ | 23G | **best overall** — the flagship |
| `…embF16-Q8_0_ROCMFPX.gguf` | 28G | maximum fidelity |
| `…embF16-Q4_0_ROCMFP4.gguf` | 19G | fastest decode (4-bit) |
| `…embF16-Q3_0_ROCMFPX.gguf` | 16G | smallest |

All filenames prefixed `Qwen3.6-27B-STRIX-`.

## Quick start

```bash
# build the fork once — main already has the ROCmFPX quant types
git clone https://github.com/charlie12345/ROCmFPX.git && cd ROCmFPX
JOBS=16 scripts/build-strix-rocmfp4-mtp.sh

# serve the flagship — MTP + vision
HSA_OVERRIDE_GFX_VERSION=11.5.1 build-strix-rocmfp4/bin/llama-server \
  -m Qwen3.6-27B-STRIX-embF16-headQ6-Q6_0_ROCMFPX.gguf \
  -dev ROCm0 -ngl 999 -fa on -c 32768 \
  --spec-type draft-mtp --spec-draft-ngl all --spec-draft-n-max 2 \
  --jinja --mmproj mmproj/mmproj-F32.gguf --host 0.0.0.0 --port 8080
```

Tool calls: serve with `--jinja` so the model's own chat template emits them — no special parser flag needed.

<details>
<summary><b>All tiers · recipe · benchmarks</b></summary>

### All tiers

| File suffix | Preset | Enum | Size | Role |
|---|---|---|---|---|
| `embF16-headQ6-Q6_0_ROCMFPX.gguf` | `Q6_0_ROCMFPX` | 110 | 23G | flagship — f16 emb + Q6_K head + imatrix |
| `embF16-Q8_0_ROCMFPX.gguf` | `Q8_0_ROCMFPX` | 111 | 28G | highest fidelity |
| `embF16-Q4_0_ROCMFP4.gguf` | `Q4_0_ROCMFP4` | 100 | 19G | fastest decode (4-bit body) |
| `embF16-Q3_0_ROCMFPX.gguf` | `Q3_0_ROCMFPX` | 112 | 16G | smallest |

f16 token embeddings throughout. (HF labels `Q4`/`Q8` but not `Q6`/`Q3` — the latter aren't standard llama.cpp quant names; pick by filename.)

### Verification (Strix Halo gfx1151)

| Metric | Value |
|---|---|
| Functional smoke | chat/coding/JSON/tool-call/coherency ✅ (5/5) |
| PPL vs `Q6_K` | flagship **5.7030** vs stock `Q6_K` **5.6618** → Δ +0.73% (general slice, ctx 512) |

### Performance — prompt-processing throughput (t/s) vs `Q6_K`

| Context | `Q6_K` | flagship | Δ |
|---|---|---|---|
| pp512 | 188 | 242 | **+29%** |
| pp2048 | 191 | 245 | +28% |
| pp10k | 180 | 228 | +27% |
| pp16k | 172 | 217 | +26% |
| pp32k | 156 | 193 | +23% |
| pp64k | 133 | 159 | **+20%** |

Clean dedicated-GPU `llama-bench` (both servers stopped, warm-up pass discarded). The gfx1151-tuned ROCmFPX kernels win the compute-bound prefill — the edge is largest at short context and narrows to +20% at 64k as O(n²) attention takes over. Decode is bandwidth-bound (≈ Q6_K raw), and **MTP (`--spec-type draft-mtp`) ~doubles it** in serving. *Single-rep `llama-bench`; treat absolutes as ±a few %.*

</details>

## Credits & license

Apache-2.0 (inherited). Qwen3.6 (base) → [charlie12345 / ROCmFPX](https://github.com/charlie12345/ROCmFPX) (quant fork). ROCmFPX quantization by this repo's author.