Tag: Qwen
Qwen3.6-27B Abliteration Benchmarked: Five Techniques Under the Microscope
Five different groups abliterated the same AI model. When I ran the maths benchmarks, their scores ranged from 27.5% to 75.1%. That is a 47.6 percentage point gap. It looks like some techniques made the model way better at maths and others broke it. But when I dug into why, it turned out nobody got smarter or dumber. The abliteration just changed how long they think before answering. The real scores were all within 2.8 percentage points of each other.
Uncensored LLM Abliteration Benchmarked: HauhauCS vs Heretic vs Huihui
HauhauCS describes their abliterated models as “the best lossless uncensored models out there” with “no changes to datasets or capabilities” and claims 0 refusals across their entire model range. I ran the full forensic suite across five Qwen models to find out whether those claims hold up.
Heretic Docker: Abliterating LLMs for Video and Image Generation
A while back I did a deep dive into abliterating Gemma 3 12B for use as an uncensored text encoder in LTX-2 video generation. The process worked but involved a lot of manual steps: running Heretic, merging safetensor shards, converting to ComfyUI format, quantizing to FP8, building GGUF quants. I got tired of doing it all by hand, so I built heretic-docker to automate the whole thing.