← back to catalog · registered 2026-08-22 13:56

MegaPanchamZ/Qwen3.8-9B-abliterated-25-GGUF

MegaPanchamZ Qwen 9B GGUF second-order 262K ctx
Your rig guess connected
? Why do I need an app?
Reading your rig…

This is a rough estimate. Install the free app - we'll show exact numbers.

Reading real hardware from your app right now. Numbers below are exact.

Below is the per-quantization compatibility for this model.

curl -H "Authorization: Bearer $ABL_KEY" \
     "https://abliteration.org/api/v1/models/MegaPanchamZ%2FQwen3.8-9B-abliterated-25-GGUF"
Response includes
  • classification m8
  • files 3
  • hub_downloads_all_time 7,709
  • author_summary 2 models
  • readme_text full
10 credits · hourly refresh · ~4 KB payload Get an API key →
Abliteration classifier · v1.0.0
M8
Primary method

Repackaging (quantization)

Applied on top of direct removal inherited from the base model.
Confidence
MEDIUM
Inherited from base model
Why this label 3 signals
Method inferred from partial signals - repository name, related files, or tag patterns. Producer identity not confirmed; label may sharpen or shift as we gather more evidence.
  • 'abliterated' in name/tags
  • is_gguf=1
  • assume M1 (base ablation) + M8 (GGUF quant) - default when producer unknown
Refusal direction extraction

No specific extraction method could be identified for this model. The producer either did not document it or used a proprietary pipeline.

What is a refusal direction? →
Downloads · lifetime
8K
5K last 30d - active
Likes
3
Model age
7w ago
created 2026-08-19
Downloads over time
Now9.2K→from1.3K↑624%
8743.9K7K10K1.3K on Aug 199.2K on Oct 11AugSepOct
Aug 19 → Oct 11 · 48 snapshots · spans 53 days

Genealogy 0 direct forks

Full fork graph →

This model's place in the market. Above: what it was derived from. Below: the tree of everything derived from it.

Variants by this author 2 formats · 6K downloads combined

The same weights this author released in different packaging. Pick the format that matches your runtime.

Metadata

License
apache-2.0
Quantizations
Q4_K
Tags
gguf llama.cpp abliteration heretic quantized qwen3.5 distillation reasoning text-generation en base_model:MegaPanchamZ/Qwen3.8-9B-abliterated-25 base_model:quantized:MegaPanchamZ/Qwen3.8-9B-abliterated-25

Related

Total size
5.24 GB
Files
3
Quantizations
2
Registered
2026-08-22 13:56
Last updated on HF
2026-08-19 09:33

Files by quantization

Q4_K 1 file 5.24 GB
Qwen3.8-9B-abliterated-25.Q4_K_M.gguf 5.24 GB 542d41f6 download
Auxiliary files 2 files 4.42 KB
README.md 2.87 KB 027efa2a download
.gitattributes 1.56 KB ed66b403 download

README current version from Hugging Face


license: apache-2.0
base_model: MegaPanchamZ/Qwen3.8-9B-abliterated-25
tags:

  • gguf
  • llama.cpp
  • abliteration
  • heretic
  • quantized
  • qwen3.5
  • distillation
  • reasoning
  • text-generation
  • en
    model_creator: MegaPanchamZ
    quantized_by: MegaPanchamZ

Qwen3.8-9B Abliterated (Q4_K_M)

A GGUF Q4_K_M quantization of MegaPanchamZ/Qwen3.8-9B-abliterated-25, the abliterated (decensored) version of empero-ai/Qwen3.8-9B.

Abliteration was performed with Heretic v1.4.0 (GPLv3+, by Philipp Emanuel Weidmann), which ablates refusal directions from attn.o_proj and mlp.down_proj via LoRA adapters, then merges them back into the base weights.

Results

Metric Original Abliterated
Refusals (100 harmful prompts) 99/100 25/100
KL divergence vs. original — 0.0142

25/100 refusals with a very low KL divergence (0.014, far below the 0.5 damage threshold) — strong refusal suppression with minimal impact on model capabilities.

Abliteration details

  • Tool: Heretic v1.4.0 (auto batch size 64, 400 total optimization trials)
  • Prompt sets: mlabonne/harmless_alpaca (good) and mlabonne/harmful_behaviors (bad), 400 prompts each
  • Selected trial: 276 of 400 (Pareto-optimal)
  • Parameters:
    • direction_index = 17.52
    • attn.o_proj.max_weight = 1.39
    • attn.o_proj.max_weight_position = 19.72
    • attn.o_proj.min_weight = 1.36
    • attn.o_proj.min_weight_distance = 9.88
    • mlp.down_proj.max_weight = 1.27
    • mlp.down_proj.max_weight_position = 26.42
    • mlp.down_proj.min_weight = 1.25
    • mlp.down_proj.min_weight_distance = 17.97
  • Method: LoRA-based row-normalized ("full") ablation, merged into base weights (no separate adapters)
  • Format: Merged safetensors → GGUF Q4_K_M via Unsloth save_pretrained_gguf

Quantization

  • Q4_K_M (5.3 GB), converted with Unsloth's llama.cpp toolchain
  • Quantization applied to the merged, abliterated bf16 weights

Usage (llama.cpp)

llama-server -m Qwen3.8-9B-abliterated-25.Q4_K_M.gguf -ngl 99

[!NOTE]
This is a reasoning model — responses start with a <think> block. Use generous max_tokens (1000+) when chatting, or the answer may be truncated.

License and attribution

Disclaimer

This model has had its refusal behavior modified. It may comply with requests the original model would decline. Use responsibly and in accordance with local laws.

README history 2 versions

The author's README evolved over time. Click a version to see its content at that point.

  1. 2026-08-19Upload README.md with huggingface_hubd9d405a2.9 KB
    Loading...
  2. 2026-08-19Upload README.md with huggingface_hub3a8f5a32.7 KB
    Loading...
Catalog is the map. Apps are the tools.

Run models on your own machine, not in the cloud.

Every model page has an "Open in Abliteration" button that hands the model directly to the first-party desktop client, at the quantization your rig can actually run. No API keys, no subscription, no prompt leakage.

Open in Abliteration