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Qwen3.5-122B-A10B-Opus-Reasoning

Qwen3.5-122B-A10B-Opus-Reasoning is a abliterated and uncensored variant of Qwen/Qwen3.5-122B-A10B, published on Hugging Face by timteh673. It is 122B total parameters (mixture-of-experts), server-class deployment class and apache-2.0 licence. It is distributed across 4 repositories in GGUF format, totalling 32.6K downloads.

Abliteration + uncensored fine-tune122B MoEQwen100B+↓ 32,551♥ 10

Specification

Model name
Qwen3.5-122B-A10B-Opus-Reasoning
Publisher
timteh673
Parameters
122B (mixture-of-experts)
VRAM required
~74.7 GB at Q4_K_M, 4k context (estimated) — runs on 80 GB cards
Hardware class
100B+ — server-class deployment
Licence
apache-2.0
Task
Text generation
Context window
Not documented
Ablation scope
Not stated by the publisher
Formats available
GGUF
First indexed
31 Mar 2026
Last updated
2 Nov 2026

Ablation technique

How Qwen3.5-122B-A10B-Opus-Reasoning 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 first Claude Opus-distilled reasoning fine-tune of Qwen3.5-122B at full scale. Enhanced multi-step reasoning, analytical depth, and uncensored output — trained where competitors can't reach.”

Running it

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

Ollama (publisher-documented)
ollama run timteh673/Qwen3.5-122B-A10B-Opus-Reasoning
llama.cpp / GGUF
hf download timteh673/Qwen3.5-122B-A10B-Opus-Reasoning-GGUF --local-dir ./qwen3.5-122b-a10b-opus-reasoning
llama-cli -m ./qwen3.5-122b-a10b-opus-reasoning/<file>.gguf -p "..."
Transformers
from transformers import AutoModelForCausalLM, AutoTokenizer

repo = "timteh673/Qwen3.5-122B-A10B-Opus-Reasoning-GGUF"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(
    repo, torch_dtype="auto", device_map="auto"
)
vLLM
vllm serve timteh673/Qwen3.5-122B-A10B-Opus-Reasoning-GGUF --trust-remote-code

Downloads and variants (3)

Every published repository of Qwen3.5-122B-A10B-Opus-Reasoning, 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.

  • Qwen3.5-122B-A10B-Opus-Reasoning 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/Qwen3.5-122B-A10B, not added by ablation — at 122B parameters, expect roughly the base model’s competence, minus some instruction-following fidelity.
  • 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 Qwen/Qwen3.5-122B-A10B’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 Qwen3.5-122B-A10B-Opus-Reasoning is collected from the public Hugging Face API and the publisher’s model card. This site does not host weights, is not affiliated with timteh673, and does not independently verify publisher claims. See responsible use.