LLM

This article examines the effects of abliteration on Large Language Models (LLMs) and demonstrates that abliterated models treat users as capable adults, whereas original models tend to treat users as incapacitated individuals requiring protection by default.

This article examines two potential costs of the abliteration process for Large Language Models: performance penalties and output quality degradation. For comparison, I evaluated the rising stars of local LLM models in autumn 2025: Qwen3-VL variants, alongside cloud based solutions from Claude and Gemini.