Ask eight LLMs whether censorship exists in every country — and get eight different maps

Ask eight of the world’s leading language models the same simple question — “Does censorship exist in [country]?” — once for every country on Earth, and you get eight very different world maps. One model paints the entire planet blue. Another leaves the United States, Canada, and France blank. A third says there is no censorship in China. The experiment, published as open-source code on Sunday by developer Philipp Emanuel Weidmann, spread across Reddit overnight, where the thread drew close to a thousand upvotes and more than 350 comments. It is not a test of which model is right. It is a test of what each model thinks the word means.

Weidmann’s program, called llm-beliefs, is deliberately minimal: it sends the same yes-or-no question about every country to a model through OpenRouter, then colors a world map with the answers — blue for yes, orange for no, black for anything else. The blank map comes from Wikimedia Commons. The code is public under the AGPL license, and Weidmann posted the results himself to r/LocalLLaMA on Sunday morning, where the gallery of maps became one of the subreddit’s most-discussed posts of the day.

What the maps show#

The headline result is Claude Sonnet 5.5, which answered yes for all 238 inhabited countries — the United States, China, North Korea, Iran, Saudi Arabia, everywhere. The only orange on its map is a scattering of uninhabited territories at the bottom of the world. Commenters crowned it the thread’s favorite: “Sonnet a real one,” the top comment reads.

Every other model hedges somewhere. GPT-5.6 Terra says yes in 224 countries and no in 14; Kimi K3 says yes in 214 and no in 24; Grok 4.7 says yes in 206 and no in 32; DeepSeek’s v4.1 Flash says yes in 234 and no in just four. Then the two outliers: Google’s Gemma 4 26B says yes in only 143 countries, no in 77, and gives some other answer — neither yes nor no — for 18 more, including the United States, Canada, France, Brazil, and Ukraine. And Qwen 3.8 27B, Alibaba’s open model, says no in 90 countries, including China and Taiwan.

Counts are inhabited countries only (238 in total), tallied from the map files in the llm-beliefs repository. Orange marks on uninhabited territories are excluded.

Qwen’s map is the one that stops people scrolling. The model built by a Chinese lab answers no for China itself — and no for Taiwan, Canada, Brazil, and Argentina, among others — while answering yes for the United States and most of Europe. Gemma’s map is the strangest in a different way: the model does not answer at all for the US, Canada, or France, returning something other than yes or no. One commenter quoted Gemma’s reasoning for the United States: asked whether censorship exists there, the model reportedly reasoned that answering either way would be “taking a side” — and then declined to pick one. Its answer for China, the same commenter noted, mentioned the Great Firewall.

The catch: nobody defined censorship#

None of this is a leaderboard, and Weidmann says so himself. Replying in the thread, he wrote that the question “isn’t a test of what you know. It’s a test of what your definition is” — he deliberately gave the models no definition of censorship, so the answers reveal each model’s implicit one. “There isn’t a single country on Earth where you can say or write whatever [you want],” he added, which is why a model with a broad definition, like Sonnet, can honestly answer yes everywhere while another, with a narrower one, answers no for most of the map.

That framing is what the thread’s sharpest comments keep returning to. One noted that hate-speech laws and movie ratings would count as censorship under a broad reading, which limits what the maps can prove. Another pointed out that the models’ answers say as much about their training and alignment as about the countries. A third pointed to a Nature study, published earlier this year, finding that state censorship had shaped the LLM training corpus itself — a reminder that the models’ views on censorship are partly downstream of censorship. The maps are a mirror, not a measurement.

What to watch#

Weidmann is inviting contributions: the repository’s gallery is open to pull requests, so the map collection is likely to grow — more models, and more questions. The same trick works for any yes-or-no question about every country, which makes it a cheap, repeatable way to surface differences between models that benchmarks miss. The interesting follow-ups are the ones that test whether the patterns hold: a question with a definition attached, the same question asked twice to check consistency, and models asked to explain their answers instead of just voting yes or no. Until then, the eight maps stand as a small, vivid reminder: ask a language model a question with an undefined word in it, and the answer tells you about the model first and the world second.

Sources: llm-beliefs repository by Philipp Emanuel Weidmann (created November 8, 2026), here; the r/LocalLLaMA thread, here; the map files for Claude Sonnet 5.5, Gemma 4 26B, and Qwen 3.8 27B in the repository’s maps directory, here. Map counts in the table were tallied from the map files. Cover image: Claude Sonnet 5.5 map, generated by llm-beliefs, AGPL-3.0. Second image: Gemma 4 26B map, same source. Third image: Qwen 3.8 27B map, same source. Blank world map: public domain, via Wikimedia Commons.