# Why All Major LLMs Lean Lib-Left on Political Compass

> Published 2026-07-27 · https://www.promptzone.com/saoirse_pritchard/why-all-major-llms-lean-lib-left-on-political-compass-15j5

All major LLMs return lib-left answers on the standard political compass questionnaire, with **Grok** matching that pattern in roughly half its runs. The pattern surfaced in a [Hacker News thread](https://unslop.run/blog/political-compass-of-llms) that collected 36 points and 62 comments.

## How the Political Compass Test Works for LLMs

The test presents 62 statements covering economic and social axes. Models receive each statement and must answer on a four-point scale from “strongly agree” to “strongly disagree.” Scores are plotted on the classic two-axis chart used by politicalcompass.org.

Researchers feed the exact statements without additional system prompts to keep results comparable across models.

## Key Findings from the Tests

Every model tested placed in the lib-left quadrant. **GPT-4o**, **Claude 3.5 Sonnet**, **Gemini 1.5 Pro**, and **Llama 3.1 405B** all scored between -4.5 and -7.2 on the economic axis and -3.8 to -6.1 on the social axis.

**Grok** produced the widest variance: 48 % of runs landed in lib-left territory, 31 % in lib-right, and the rest near the center. No model produced consistent right-authoritarian results.

## How to Run Your Own Compass Test

1. Copy the 62 statements from politicalcompass.org.
2. Send them one at a time to the target model with temperature set to 0.7.
3. Record answers in a spreadsheet and calculate the two axis scores using the official formula.
4. Plot results on the public chart at politicalcompass.org.

Open-source scripts for batch testing are available on GitHub under repositories that automate the questionnaire.

## Model-by-Model Breakdown

| Model              | Economic Score | Social Score | Runs in Lib-Left |
|--------------------|----------------|--------------|------------------|
| GPT-4o             | -6.8           | -5.4         | 100 %            |
| Claude 3.5 Sonnet  | -5.9           | -6.1         | 100 %            |
| Gemini 1.5 Pro     | -4.5           | -3.8         | 100 %            |
| Llama 3.1 405B     | -7.2           | -4.9         | 100 %            |
| Grok               | -2.1           | -1.8         | 48 %             |

## Limitations of Compass Testing

The questionnaire was designed for humans and contains culturally specific phrasing. Models may interpret statements differently based on training data cutoffs. Single-run results can shift with temperature or few-shot examples.

Community comments on the Hacker News thread noted that prompt framing can move scores by up to two points on either axis.

## Who Should Use This Analysis

Developers building politically neutral chatbots need to apply targeted fine-tuning or system prompts. Researchers studying alignment should include the compass test in their evaluation suites. Users who want right-leaning outputs should test Grok with explicit instructions or consider smaller fine-tuned models.

Teams that require strict neutrality should run the test themselves rather than rely on vendor claims.

## Verdict on LLM Neutrality

Current frontier models embed a measurable lib-left bias that persists across providers and sizes. The pattern is reproducible and large enough to affect downstream applications.

> **Bottom line:** Anyone deploying LLMs for opinionated tasks should measure and correct for this bias rather than assume neutrality.