uncensored

AtomicChat released GSQ-RCO GGUF quantizations of DeepSeek-V4.1-Flash-1017 with refusal directions projected out of the dense residual writers, letting a 763B MoE model run on a single 12 GB GPU via Strata with minimal MMLU degradation.

Release of Swift 1.5 Flash Next - Heretic v2, a custom GGUF quantization of Qwen 3.8 Flash optimized for reverse engineering and coding, featuring new heretic weights and a layer-aware bit allocation strategy based on activation-energy auditing.

A Hugging Face release of DeepSeek-V4.1-Flash-1017 with refusal behavior removed via abliteration, shipped in native FP8 (e4m3) weights with FP4 MoE experts while preserving vision, video, tool calling, reasoning tiers, and 1M-token context. The model card emphasizes it is not a quantized derivative, not a chat-template jailbreak, and not LoRA/RLHF-based — the edited weights are the model.

A Hugging Face release packaging HauhauCS's uncensored Qwen3.8-27B weights with DavidAU's Turbo-Brilliance 'AI Construct' chat template modes into a single GGUF, enabling role-based uncensored responses in llama.cpp, LM Studio, and Ollama.

An introduction to AtomicChat's "decensored" text encoder for Qwen-Image-2.1-Turbo, released on HuggingFace in GGUF quantized form, plus a complete tutorial for running it locally with ComfyUI on 8GB VRAM (RTX 5060). Includes the full file download checklist, node configurations, 5 real-world gotchas with their fixes, and prompt examples.

AtomicChat 发布了 Qwen-Image-2.1-Turbo 的无审查（uncensored）GGUF 量化版本，量化阶梯从 3.3 GB 到 16.4 GB，可使用 llama.cpp、Ollama、LM Studio 等工具在本地运行图像生成。

AtomicChat released an abliterated GGUF of Qwen-Image-2.1-Turbo's text encoder (Qwen3-VL-8B-Instruct) with the refusal direction projected out, dropping chat refusals from 88.9% to 1.2% with no measurable MMLU loss. Benchmarks on 45 sensitive prompts show no change in image output, since the stock Qwen-Image pipeline has no safety checker.

Abenzerps 发布了 Qwen-Image-2.1 的去审查量化版本，提供 GGUF、Safetensors 和 MLX 格式，支持在 ComfyUI 中进行本地图像生成，Q4_K_M 为推荐量化档位。

GGUF quantizations of the Qwen-Image-2.1 model for local image generation using ComfyUI, with recommended quantizations and setup instructions for deployment.

A user questions whether uncensored AI models perform better for coding due to fewer content restrictions, seeking evidence and anecdotes from the community.

A permanently modified version of DeepSeek-V4.1-Flash with surgically removed safety guardrails, retaining full capabilities including vision, reasoning, and tools, and demonstrating 100% compliance on HarmBench evaluations.

CyberTiel 35B-A3B is an uncensored 4-bit quantized AI model optimized for coding tasks, outperforming Opus 4.6 medium and being significantly faster than Qwen3.8-27b medium on real codebase issues.

This article presents a comprehensive benchmark of 8 abliterated variants of the Qwen 3.8 27B model against the base model, using weight analysis, KL divergence, 13 benchmarks, and HarmBench refusal tests over 167 GPU hours. The analysis reveals that surgical edits significantly outperform heavy modifications, with aggressive abliteration causing thinking loops in up to 45% of adversarial responses and chat template manipulation detected in some variants.

A fine-tuned version of Qwen3.8-27B that significantly reduces thinking tokens while exceeding key AI benchmarks like ARC-C and ARC-E, optimized for consumer hardware.

dealignai released a cybersecurity-focused weight-modified variant of the 753B-parameter GLM-5.3-FP8 model that reduces refusals for offensive-security tasks such as red-teaming, exploit development, and malware analysis while preserving base capabilities and running natively on Hopper GPUs via stock vLLM.

This article describes an uncensored version of Z.ai's GLM-5.3-Flash model, with safety alignments removed via abliteration, released as a block-FP8 checkpoint for research purposes.

Nous Research releases gpt4-x-vicuna-13b, a Vicuna model trained on over 180k uncensored GPT-4 outputs, with plans to further remove OpenAI censorship.

This article releases GGUF quantizations of the uncensored Qwen3.8-Flash-Next model, a Mixture-of-Experts preview of the Qwen4 architecture designed for llama.cpp with vision support, requiring a custom build for compatibility.

The Qwen3.8-27B-Uncensored is a 27B-parameter AI model with safety alignment removed via abliteration, released on Hugging Face for research purposes without built-in guardrails.

This article shares three uncensored quantized versions of the Qwen3.8-27B model for local deployment. The author has personally tested them and warns to use with caution.