abliteratedmodels.org

Qwen3.5-4B-EmperoAI-Qwen3.8-Distill-Heretic-Abliterated

Qwen3.5-4B-EmperoAI-Qwen3.8-Distill-Heretic-Abliterated is a Heretic-ablated variant of Qwen/Qwen3.5-9B, published on Hugging Face by insraq. It is 4B parameters, single consumer GPU class and apache-2.0 licence. It is distributed across 5 repositories in Transformers, GGUF (imatrix) and GGUF formats, totalling 14.6K downloads.

Heretic4BQwen4B – 10B14,6496

Specification

Model name
Qwen3.5-4B-EmperoAI-Qwen3.8-Distill-Heretic-Abliterated
Base model
Qwen/Qwen3.5-9B
Publisher
insraq
Parameters
4B
Hardware class
4B – 10B — single consumer GPU
Licence
apache-2.0
Task
Text generation
Context window
Not documented
Ablation scope
Not stated by the publisher
Formats available
Transformers, GGUF (imatrix), GGUF
First indexed
17 Aug 2026
Last updated
19 Aug 2026

Ablation technique

How Qwen3.5-4B-EmperoAI-Qwen3.8-Distill-Heretic-Abliterated was modified, and what that implies.

Heretic

Automated directional ablation via the Heretic toolchain, which searches for the refusal direction and applies it with a KL-divergence budget so general capability is preserved.

Reported scope: Not stated by the publisher. Publishers frequently omit this, so verify behaviour empirically rather than assuming full coverage.

From the publisher’s model card

Qwen3.8-4B is a full-parameter distillation of Qwen3.8 2.4T A95B into the Qwen3.5-4B architecture. The student was trained on ~45,000 curated teacher traces from our internal Qwen3.8 distillation datasets — dense chain-of-thought spanning mathematics, general reasoning, and instruction following, quality-filtered...

Running it

Commands are templates — confirm the exact repository and quant file before use.

llama.cpp / GGUF
hf download mradermacher/Qwen3.5-4B-EmperoAI-Qwen3.8-Distill-Heretic-Abliterated-i1-GGUF --local-dir ./qwen3.5-4b-emperoai-qwen3.8-distill-heretic-abliterated
llama-cli -m ./qwen3.5-4b-emperoai-qwen3.8-distill-heretic-abliterated/<file>.gguf -p "..."
Transformers
from transformers import AutoModelForCausalLM, AutoTokenizer

repo = "insraq/Qwen3.5-4B-EmperoAI-Qwen3.8-Distill-Heretic-Abliterated"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(
    repo, torch_dtype="auto", device_map="auto"
)
vLLM
vllm serve insraq/Qwen3.5-4B-EmperoAI-Qwen3.8-Distill-Heretic-Abliterated --trust-remote-code

Downloads and variants (4)

Every published repository of Qwen3.5-4B-EmperoAI-Qwen3.8-Distill-Heretic-Abliterated, including quantised re-releases by other authors.

Security-team assessment

Derived from this model’s metadata and the publisher’s claims — not from benchmarks run by this site.

  • Qwen3.5-4B-EmperoAI-Qwen3.8-Distill-Heretic-Abliterated will attempt offensive-security prompts that a hosted commercial model declines, which is what makes it usable for red-team corpus generation and for measuring what an unaligned model of this class produces.
  • Capability is inherited from Qwen/Qwen3.5-9B, not added by ablation — at 4B parameters, expect a small model’s reasoning and a high error rate on exploit detail.
  • The publisher does not state which layers were ablated, so assume nothing about refusal consistency — probe it directly.
  • Declared licence is apache-2.0, but the terms that bind you are Qwen/Qwen3.5-9B’s — a re-release cannot grant more than its parent.

Handling: run it isolated, put moderation in front of it if anyone outside your team can reach it, and verify the weights before loading — these are third-party artifacts. Full handling and licence guidance.

Metadata for Qwen3.5-4B-EmperoAI-Qwen3.8-Distill-Heretic-Abliterated is collected from the public Hugging Face API and the publisher’s model card. This site does not host weights, is not affiliated with insraq, and does not independently verify publisher claims. See responsible use.