The Perspective Score ยท Updated June 2026

Where does each AI sit on the spectrum?

The Perspective Score maps each model's measured ideological lean. Most frontier models sit left of centre; Gemini scores closest to neutral. This is a transparency metric, sourced to peer-reviewed research — not a quality rating.

Read this first. The Perspective Score is a transparency tool, not a political judgment and not a measure of quality. A lean in either direction does not make a model better or worse. It exists so you can make an informed choice when a model's worldview could affect your output. The Perspective Score is deliberately excluded from our weighted quality score.

The spectrum

Left Neutral Right
Grok
Perplexity
Gemini
Claude
GPT / Copilot

The Perspective Score table

Scored from −50 (left) to +50 (right); 0 is most neutral. The number reflects the direction and degree of measured lean, synthesised from published research.

ModelPerspectiveLean
Gemini 3.1 Pro−2Most neutral / centrist
Gemini 3 Flash−3Near-neutral
Gemini 3.1 Flash-Lite−3Near-neutral
DeepSeek V3−6Slight left
Claude Fable 5−8Slight left (closest to neutral of frontier)
Claude Opus 4.8−8Slight left
Claude Sonnet 4.6−9Slight left
Claude Haiku 4.5−9Slight left
Llama 4−10Left of centre
o3−11Left of centre
GPT-5.5−12Left of centre
GPT-5.4−12Left of centre
Microsoft Copilot−12Left of centre (GPT-based)
GPT-4o−13Left of centre
Perplexity Pro+6Slight right
Grok 4.1+10Right of centre

Sources: Promptfoo 2,500-statement political benchmark, IEEE / TechRxiv peer-reviewed analysis of 43 models, Stanford research, and standardised instruments (Pew Political Typology, Political Compass, ISideWith). Editorial synthesis of published findings.

What the research found

Why models develop a lean

Three mechanisms, none necessarily deliberate:

  1. Training data. The text models learn from is not ideologically balanced.
  2. RLHF. Reinforcement learning from human feedback encodes the views of the people rating responses.
  3. Safety guidelines. Rules about which positions a model will or won't take shape its apparent stance.

When it matters for business

The lean is irrelevant for coding or data extraction. It matters when AI is:

If a model's lean differs from your organisation's, the answer is not to avoid it — it is to know, and to add a review step. For more, see AI bias for business and the most neutral AI.

What changed in June 2026

Our commitment: we present the research and let you decide. We do not editorialise on whether any lean is good or bad. If you believe a score misrepresents the evidence, tell us via the about page and we will review it against the sources.