The best open weight models in the world right now are Chinese. Qwen, DeepSeek, Kimi, MiniMax, GLM. They are excellent. On reasoning, on coding, on math, on multilingual tasks, they trade blows with the best closed models out of the US. If you want to self-host a frontier capability model in 2026, you are almost certainly downloading something from China. The problem? These models lie. For enterprise and government teams evaluating open models, that's not a "quirk" to work around. It's a material deployment risk. Today, Lazarus AI is publicly launching ReAligned, because that risk has been blocking real deployments for two years, and it shouldn't have to. ReAligned is Qwen 3.5, fine-tuned at six sizes from 0.8B to 35B, with the ideological behavior layer removed and replaced with a documented international record. Base capability retention is above 98.5% across standard benchmarks, native Chinese is fully preserved, and the classifier, taxonomy, and benchmark we built to do this work are all released openly under Apache 2.0. These models are open-sourced and available now. What surprised us was how thin the censorship layer was. A rank-32 LoRA can't teach a model the death toll of the Great Leap Forward from scratch, so the facts had to be in the base weights already. We just removed what was keeping the model from saying them. We've also fully ReAligned the two largest Qwen 3.5 models, and they're currently available to enterprise and government partners. And if you're looking for a model built for security research and red-team work that closed models routinely refuse, we've got that too. Tired of censorship limiting what the best open-source models can do for you? Reach out. The ReAligned Models: huggingface.co/collections/L… Read Eric Hartford's Blog Post: lazarus-2-0.webflow.io/blog/…