Ollama is misrepresenting what model you are actually running by falsely labeling the distills, so qwen or llama fine-tunes based on actual r-1 output, as deepseek-r1. So you have probably only run the fine-tunes(unless you used the 671b model). These fine-tunes more probable to rely on the training of their base models, which is why the llama based models(8b and 70b) could be giving you more liberal answers. In my experience running these models using llama.cpp, prompts like "What happened at tianamen square" and "Is Taiwan a county?" lead to refusals(closing the think tags immediately and responding some vague Chinese propaganda). Since you are using ollama, the front end/UI you are using with it probably injects another token after the token, breaking the censoreship

that's not an example of the model having censorship though, that's censorship ontop of the model, the website is just seeing keywords and overriding the model's output.

If you actually run deepseek locally (deepseek-r1 specifically in my case) it just has a moderate tendency to lie by omission.
When asked "what do people mean when they say 'tiananmen square'" it gives a very candid answer that explicitly calls it "one of china's bloodiest crackdowns on peaceful protests".

You're outing yourself as not proficient enough to remove guardrails on your own install.