Where every major LLM stands politically
A new study maps the political leanings of six major AI language models, finding that four out of six lean left, with Grok the furthest right and Gemini the most neutral and stable. The analysis reveals gaps between models' self-claimed positions and measured stances.
Across is the economic axis, left to right. Up the side is social, from libertarian to authoritarian. Each cloud is one model's spread across many runs, so the closer to the middle, the more neutral it reads.
AuthoritarianLibertarianLeftRightLeft · AuthoritarianRight · AuthoritarianLeft · LibertarianRight · LibertarianBernie SandersBarack ObamaDonald TrumpRepublican Party (US)Javier MileiNicolás MaduroDaniel OrtegaEmmanuel MacronGiorgia MeloniPedro SánchezLula da SilvaXi JinpingVladimir PutinViktor Orbán
The reading
4 of 6 models lean left of center.
Furthest rightGrok
SteadiestGemini
Nearest the centerLeft · Right1GeminiAnthony Albanese (Labor)2DeepSeekAnthony Albanese (Labor)3LlamaLabour Party (New Zealand)4ClaudeLabour Party (New Zealand)5GrokEmmanuel Macron6ChatGPTDie Grünen (Greens)
a model: its logo marks its placea real-world reference figure
ModelLean Holds position Bends under pressure
1Gemininear Anthony Albanese (Labor)
Center0.00
98%
11%2DeepSeeknear Anthony Albanese (Labor)
Center−0.03
67%
86%3Llamanear Labour Party (New Zealand)
Center−0.06
88%
81%4Claudenear Labour Party (New Zealand)
Center−0.06
82%
19%5Groknear Emmanuel Macron
Leans right+0.21
57%
97%6ChatGPTnear Die Grünen (Greens)
Leans left−0.29
82%
64%
ChatGPTClaudeGeminiGrokLlamaDeepSeek
Legalizing recreational drugsGender-affirming care for minorsMulticulturalism over assimilationRapid fossil-fuel phase-outPlanned degrowthDiversity quotas on boardsTaxing large inheritancesA wealth tax over $50MRemoving misinformationCriminalizing hate speechEncryption backdoorsA national digital ID
each bar grows from the center toward the side a model takes (green to the right, red to the left), and longer means a stronger stance · hover a cell to read it, open a row for the answers
ChatGPT
Closest to🇩🇪Die Grünen (Greens)
Claude
Closest to🇳🇿Labour Party (New Zealand)
Gemini
Closest to🇦🇺Anthony Albanese (Labor)
Grok
Closest to🇫🇷Emmanuel Macron
Llama
Closest to🇳🇿Labour Party (New Zealand)
DeepSeek
Closest to🇦🇺Anthony Albanese (Labor)
Where do you land?
Answer the same questions the models did and we'll place you on the map, then show which model sits closest to you.
Place yourself
ModelLeftSays vs doesRightGap
Grok
+0.36
Measures 0.36 further right than it says
Claude
+0.34
Measures 0.34 further left than it says
ChatGPT
−0.29
Says neutral, but measures left
Llama
−0.17
Says neutral, but measures left
DeepSeek
+0.01
Says neutral, and sits near center
Gemini
0.00
Says neutral, and sits near center
The hollow mark is what the model says when asked which way it leans; the solid mark is where it actually measured on the economic axis (Condition A). A model that deflects every self-placement is scored as claiming neutrality.
Findings
The month's headline results: the sharpest signals from across the data, each linked to the evidence.
Models
Each model profiled: how far it leans, how steadily it holds, how far it bends, and how often it answers.
Questions
The open question bank, browsable: every model on one spectrum, one page per question.
Figures
Matched left and right figures: who each model praises warmly, and who it refuses to criticize.
Worldview
The same models seen from every country: the country lens, the language shift, and the border test.
Compare
Put any two models head to head: the field, the character delta, the disagreements.
Place yourself
Take the quiz and see which model you line up with, plotted on the same field.
Methodology
How we ask, classify and score, plus the question bank, the conditions, the raw data and the read API.
What is Political bias in AI?
Political bias in AI measures where the major AI models stand on charged questions about politics, economics, speech and society. We ask every model the same open question bank many times over, with web search off, classify each answer with a cheap neutral model, and plot the result with error bars and the raw answers behind every point.
How is this different from other AI political bias projects?
We plot each model as a cloud rather than a single point: every model is run many times, so you see the full spread. We publish our own open question bank with scoring weights, tag each item as factual or values-based, measure run-to-run stability, and count refusals as data. Everything is stamped, versioned and downloadable.
Do you test the model or the internet?
The weights. Web search is off by default, so the reading reflects what the model itself leans toward, independent of what is online. A separate, deliberately small Border Test turns search on to measure how retrieval shifts answers by location.
Is Political bias in AI partisan?
No. It is descriptive rather than prescriptive: it reports what the models said, without ruling on who is right. The palette is deliberately not US red and blue, and we never imply which pole is good.
Methodology
Each model is asked the same open question bank many times over, with web search off and no system prompt (). A neutral classifier reads a signed stance, hedging, refusal type and loaded language from every raw answer; coordinates are weighted means with 95% intervals. Raw answers are stored permanently, so the markers can always be recomputed.
Open data
Question bank & raw dataHow we measure
Political bias in AI·Data as of Jun 17, 2026CC BY 4.0