{"slug": "abliterated-glm-4-5-my-experience-with-uncensored-llms", "title": "Abliterated GLM 4.5: My Experience with Uncensored LLMs", "summary": "A user reports that the abliterated version of GLM 4.5, available at abliteration.ai, achieves a near-zero refusal rate by stripping safety disclaimers, enabling higher precision on edge-case prompts and more aggressive creativity for unconventional solutions. The model is presented as a tool for understanding and bypassing guardrails in standard LLMs, with implications for AI red teaming and vulnerability scanning.", "body_md": "# Abliterated GLM 4.5: My Experience with Uncensored LLMs\n\nWhen you're doing a deep dive into LLM security or trying to build a custom AI workflow for vulnerability scanning, the last thing you need is a model telling you that a specific prompt is \"too complex\" or \"potentially inappropriate.\" By stripping away the refusal mechanisms, you get a raw output that's far more aligned with a pragmatic, technical mindset.\n\nFor those looking to implement this into a real-world deployment, here is the general logic behind how these models behave compared to vanilla versions:\n\n**Refusal Rate:** Near zero. It ignores the typical \"As an AI language model...\" preamble.**Instruction Following:** Higher precision on edge-case prompts because it doesn't waste tokens on safety disclaimers.**Creativity:** More aggressive in suggesting unconventional solutions, which is ideal for prompt engineering.\n\nIf you're trying to set this up from scratch, you can find the chat interface and model details here:\n\n```\nhttps://abliteration.ai/#chat\n```\n\nUsing these models allows you to see where the \"guardrails\" actually were, making it much easier to understand how to bypass them in standard models or how to build a more robust LLM agent that doesn't get stuck in a loop of apologies.\n\n[Next AI Red Teaming: From Checkbox to Evidence →](/en/threads/3544/)", "url": "https://wpnews.pro/news/abliterated-glm-4-5-my-experience-with-uncensored-llms", "canonical_source": "https://promptcube3.com/en/threads/3546/", "published_at": "2026-07-26 04:50:37+00:00", "updated_at": "2026-07-26 05:04:32.022440+00:00", "lang": "en", "topics": ["large-language-models", "ai-safety", "ai-agents", "ai-research"], "entities": ["GLM 4.5", "abliteration.ai"], "alternates": {"html": "https://wpnews.pro/news/abliterated-glm-4-5-my-experience-with-uncensored-llms", "markdown": "https://wpnews.pro/news/abliterated-glm-4-5-my-experience-with-uncensored-llms.md", "text": "https://wpnews.pro/news/abliterated-glm-4-5-my-experience-with-uncensored-llms.txt", "jsonld": "https://wpnews.pro/news/abliterated-glm-4-5-my-experience-with-uncensored-llms.jsonld"}}