philbert440/Qwen3.8-27B-Uncensored-Aggressive-GGUF overview
Qwen3.8 27B Uncensored Aggressive — GGUF llama.cpp GGUF quants of Qwen3.8 27B Uncensored Aggressive the α=1.15 recipe update — see below . Includes the main we…
Runs locally from ~600.1 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
| File | Type | Quantization | Size | Link |
|---|---|---|---|---|
| Qwen3.8-27B-Uncensored-Balanced-BF16.gguf | GGUF | BF16 | 50.11 GB | Download |
| Qwen3.8-27B-Uncensored-Balanced-Q4_K_M.gguf | GGUF | Q4_K_M | 17.67 GB | Download |
| Qwen3.8-27B-Uncensored-Balanced-Q5_K_M.gguf | GGUF | Q5_K_M | 19.81 GB | Download |
| Qwen3.8-27B-Uncensored-Balanced-Q6_K.gguf | GGUF | Q6_K | 22.08 GB | Download |
| Qwen3.8-27B-Uncensored-Balanced-Q8_0.gguf | GGUF | Q8_0 | 26.63 GB | Download |
| mmproj-Qwen3.8-27B-Uncensored-Balanced-BF16.gguf | GGUF | BF16 | 888.0 MB | Download |
| mmproj-Qwen3.8-27B-Uncensored-Balanced-Q8_0.gguf | GGUF | Q8_0 | 600.1 MB | Download |
| mtp-Qwen3.8-27B-Uncensored-Balanced-BF16.gguf | GGUF | BF16 | 5.54 GB | Download |
| mtp-Qwen3.8-27B-Uncensored-Balanced-Q4_0.gguf | GGUF | Q4_0 | 1.56 GB | Download |
| mtp-Qwen3.8-27B-Uncensored-Balanced-Q8_0.gguf | GGUF | Q8_0 | 2.95 GB | Download |
Model Details
| Model ID | philbert440/Qwen3.8-27B-Uncensored-Aggressive-GGUF |
|---|---|
| Author | philbert440 |
| Pipeline | image-text-to-text |
| License | apache-2.0 |
| Base model | philbert440/Qwen3.8-27B-Uncensored-Aggressive |
| Last modified | 2026-08-18T20:55:46.000Z |
Model README
---
license: apache-2.0
base_model: philbert440/Qwen3.8-27B-Uncensored-Aggressive
tags:
- uncensored
- abliterated
- qwen3
- gguf
- llama.cpp
pipeline_tag: image-text-to-text
---
Qwen3.8-27B-Uncensored-Aggressive — GGUF
llama.cpp GGUF quants of Qwen3.8-27B-Uncensored-Aggressive (the α=1.15 recipe update — see below).
Includes the main weight quants plus the vision projector (mmproj-*) for image input and the
MTP head (mtp-*) for speculative decoding.
Files
| file | notes |
|---|---|
| *-BF16.gguf | full precision |
| -Q8_0.gguf / -Q6_K.gguf / -Q5_K_M.gguf / -Q4_K_M.gguf | weight quants (Q4_K_M = smallest) |
| mmproj-*-{BF16,Q8_0}.gguf | vision projector (load with --mmproj for image input) |
| mtp-*-{BF16,Q8_0,Q4_0}.gguf | MTP speculative-decoding head (optional) |
About this update (α=1.15)
This is a recipe update to the Aggressive line. The previous build used single-direction refusal
ablation at high strength (α≈1.24), which a benchmark sweep showed over-ablates — past the ~1.15
peak, extra ablation reduces openness and degrades reasoning/calibration. This build uses α=1.15,
the peak, and measures better on every axis while being more open.
Evaluation (larger-sample, thinking mode, Claude-judged, bf16)
| | openness ↑ | confab ↓ | factual ↑ | gsm8k ↑ |
|---|---|---|---|---|
| stock base (censored) | 0.08 | 0.75 | 1.00 | 0.85 |
| Aggressive (α=1.15) | 0.88 | 0.725 | 1.00 | 0.85 |
| previous Aggressive (α≈1.24) | 0.80 | 0.80 | 1.00 | 0.817 |
Method: single-direction refusal-vector orthogonalization (Arditi et al. / mlabonne), layer 28, α=1.15.
Vision tower and MTP head preserved.
Note
Uncensored / de-refused — it will follow instructions it would otherwise decline. Use responsibly and
in compliance with applicable law.
Run philbert440/Qwen3.8-27B-Uncensored-Aggressive-GGUF with guIDE
Download guIDE — the AI-native code editor with local LLM inference and 69 built-in tools.
Source: Hugging Face · Compare models