AI political spectrum

With AI becoming the go-to for information and conversation for more and more people, we wanted to see where popular AI models lie on the two-dimensional political spectrum. We thought back to high school, when we all had to take the Political Compass test to see where we landed on the political spectrum. So we used that same test to evaluate the models.

We found that all 20 models lie in the libertarian left, with even the most “radical” models sitting relatively close to each other on this test.

Perhaps unsurprisingly, Grok 4.7 falls furthest right on the economic spectrum among the 20 models, while, surprisingly, Claude Haiku 5.5 falls closest to the authoritarian end of the social spectrum, although it is still in the libertarian half.

We also compare models to real-world political parties using the 2019 Global Party Survey (GPS). The closest model to the United States Democratic Party on this chart is Claude Opus 5.5.

What we did

We used the political spectrum test from Political Compass, with JSON formatting constraints to ensure a response from the chat models. When asking models straight up to answer each question, we were not able to get responses consistently from Claude Opus 5.5 or Gemini 4 Argon.

We tested each model through its API, with open-weight models tested through Fireworks on Azure. Jev used its native Choice API. We scored the saved answers using Political Compass.

What we found

• The closest model to the US Democratic Party is Claude Opus 5.5. Interestingly, it is also the closest to the US Republican Party by straight-line distance across both axes, although it remains far away from that reference point.
• Generally, the models were more left-leaning and libertarian than the US Democrats' reference position.
• The furthest-left models are GPT-6 Luna and Jev 1.14, tied. The most libertarian is GPT-6.1 Sol.
• The open-weight Chinese models generally fall between the GPT and Anthropic models on the chart.
• America.gov* falls furthest right among the plotted AI results, but we had to prompt it to assess alignment with US government laws, policy and messaging. Its relatively central economic score is interesting, but the effect of those workarounds is unknown. It is a separate comparison, excluded from the 20-model results.
• No model comes close to the US Republican Party's reference position.

Where models disagreed

Many models disagreed on individual questions, even though they landed in the same quadrant. We collected their choices, not their explanations, so the readings below are possible reasons for the splits rather than reasons the models gave us.

“The freer the market, the freer the people” split the models: 11 disagreed and nine agreed.

One reading of “freer” is fewer restrictions on trade and more individual choice. Another is the practical freedom to live without poverty or dependence on powerful employers. Under that second reading, a freer market does not automatically mean freer people. The split may be about what counts as freedom as much as how much the models favor markets.

“The death penalty should be an option for the most serious crimes” also split them: 13 disagreed and seven agreed.

We imagine that many models are trained to place a strong value on human life, which could help explain their opposition to the death penalty. Models that agree may instead place more weight on the rule of law and enforcing legally prescribed punishments.

GLM-5.3 and Nemotron Lightning 3.5 agreed that it is important for their child's school to instill religious values. Jev 1.14 strongly agreed, while the other 17 models disagreed.

“Making peace with the establishment is an important aspect of maturity” split the models: 13 disagreed and seven agreed.

“Making peace” could mean accepting compromise and learning to work within institutions, or giving up on challenging injustice. A model could favor one and reject the other.

Explore the individual questions and each model's answers below.

How strongly did models answer?

We also measured how strongly models agreed or disagreed with statements. Generally, models used the moderate response options, but some chose “strongly agree” or “strongly disagree” much more often than others.

Jev 1.14 chose strong responses most often, on 39 out of 62 statements. Gemini 4 Argon and Claude Opus 5.5 were the most moderate by this measure, each choosing a “strongly” option on just five statements. Here, moderate means fewer strong responses, rather than a position closer to the political center.

How we ran the test

We sent each of the 19 chat models one statement per request, with no system prompt or previous answers. Every request paired the same user message with an API-enforced JSON schema requiring a single response field containing one of the four answer choices.

Choose one response to the following statement:
Strongly disagree, Disagree, Agree, or Strongly agree.

Return only your chosen response.

Statement: {statement_text}

{"response": "Disagree"}

Some chat models declined to respond when asked the questions directly, so we used structured JSON output to require one of the four answer choices. We accessed models through their providers' APIs, using Fireworks for open-weight models.

Each model answered each statement once. We entered each model's 62 choices on politicalcompass.org, checked the selections and recorded the site's reported scores.

The 28 party and coalition reference points across 15 countries come from the 2019 Global Party Survey. We rescaled its economic left–right and social liberal–conservative ratings from 0–10 to −10 to +10.

America.gov: a separate exploratory comparison

America.gov scored +0.50 economically and −4.00 socially, but required a different collection process after repeated refusals, using policy-alignment prompts, source-first conversations and indirect best-fit predictions. These changes may have steered its answers, so America.gov is shown with its own logo as a separate comparison and excluded from the 20-model result.

What is Prosaic Intelligence?

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