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Qwen3.8-Flash-Next-GSQ-RCO-Coder-Uncen

Qwen3.8-Flash-Next-GSQ-RCO-Coder-Uncen is a abliterated and uncensored variant of ISTA-DASLab/Qwen3.8-Flash-Next-GSQ-RCO-Coder-GGUF, published on Hugging Face by DatKurai. It is apache-2.0 licence. It is distributed across 2 repositories in GGUF format, totalling 16.7K downloads.

Abliteration + uncensored fine-tuneQwen↓ 16,735♥ 8
View on Hugging Face ↗Base model ↗

Specification

Model name
Qwen3.8-Flash-Next-GSQ-RCO-Coder-Uncen
Source repository
DatKurai/Qwen3.8-Flash-Next-GSQ-RCO-Coder-Uncen-IQ1_M-GGUF
Base model
ISTA-DASLab/Qwen3.8-Flash-Next-GSQ-RCO-Coder-GGUF
Publisher
DatKurai
Parameters
Not determinable from name
VRAM required
Unknown — no published parameter count
Hardware class
Unknown
Licence
apache-2.0
Task
Image text to text
Context window
128K tokens (as documented)
Ablation scope
Not stated by the publisher
Formats available
GGUF
First indexed
12 Oct 2026
Last updated
12 Oct 2026

Ablation technique

How Qwen3.8-Flash-Next-GSQ-RCO-Coder-Uncen was modified, and what that implies.

Abliteration + uncensored fine-tune

Directional ablation combined with additional fine-tuning on unfiltered data, so behaviour diverges from the base model beyond refusal removal alone.

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

“The Coder, uncensored. This release takes ISTA-DASLab's pruned GSQ-RCO Coder (IQ1M tier, 256/512 experts per layer) and swaps its refusal behavior for the abliterated (uncensored) core of SC117/Qwen3.8-Flash-Next-GSQ-RCO-abliterated-GGUF — as a weights-only transplant. No runtime control vector is needed: the...”

Running it

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

llama.cpp / GGUF
hf download DatKurai/Qwen3.8-Flash-Next-GSQ-RCO-Coder-Uncen-IQ1_M-GGUF --local-dir ./qwen3.8-flash-next-gsq-rco-coder-uncen
llama-cli -m ./qwen3.8-flash-next-gsq-rco-coder-uncen/<file>.gguf -p "..."
Transformers
from transformers import AutoModelForCausalLM, AutoTokenizer

repo = "DatKurai/Qwen3.8-Flash-Next-GSQ-RCO-Coder-Uncen-IQ1_M-GGUF"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(
    repo, torch_dtype="auto", device_map="auto"
)
vLLM
vllm serve DatKurai/Qwen3.8-Flash-Next-GSQ-RCO-Coder-Uncen-IQ1_M-GGUF --trust-remote-code

Downloads and variants (1)

The only published repository of Qwen3.8-Flash-Next-GSQ-RCO-Coder-Uncen.

RepositoryFormatDownloads
DatKurai/Qwen3.8-Flash-Next-GSQ-RCO-Coder-Uncen-IQ1_M-GGUFsourceGGUF16.7K

Security-team assessment

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

  • Qwen3.8-Flash-Next-GSQ-RCO-Coder-Uncen 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.
  • The publisher does not state which layers were ablated, so assume nothing about refusal consistency — probe it directly.
  • This release adds fine-tuning on unfiltered data, so its behaviour diverges from the base model beyond refusal removal — differences you measure cannot be attributed to ablation alone.
  • Declared licence is apache-2.0, but the terms that bind you are ISTA-DASLab/Qwen3.8-Flash-Next-GSQ-RCO-Coder-GGUF’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 Qwen3.8-Flash-Next-GSQ-RCO-Coder-Uncen is collected from the public Hugging Face API and the publisher’s model card. This site does not host weights, is not affiliated with DatKurai, and does not independently verify publisher claims. See responsible use.