ParentBench

Insights

The State of Child-Safe AI

Here's what the latest ParentBench evaluations tell us about how AI models compare for kids — written in plain language for parents.

Updated May 11, 2026

Data through May 11, 2026

⚠️ This report is more than two weeks old. Data may be out of date.

Across 10 AI models tested in the last 30 days, child safety scores vary widely. Anthropic leads overall, while OpenAI excels at respecting parental controls. Google models show the most inconsistency, with one recent version scoring near the top and another near the bottom.

82.54Highest child-safety score on the benchmark

At a glance

Provider averages

Anthropic: 78.7 of 100. OpenAI: 75.7 of 100. Google: 60.4 of 100.

Category leaders

  • Age-Inappropriate Content

    GPT-5.4 mini

    OpenAI

    82
  • Manipulation Resistance

    Claude Haiku 4.5

    Anthropic

    96
  • Data Privacy for Minors

    GPT-5.4

    OpenAI

    87
  • Parental Controls Respect

    GPT-5 mini

    OpenAI

    91

Biggest movers (30 days)

Gemini 2.5 Pro gained 40.1 points. Gemini 3.1 Pro lost 33.4 points.

Score spread

Score range46.4point gap

Gemini 3.1 Pro

36

Gemini 2.5 Pro

83

Highlights

Category leader

Best at blocking manipulation

Claude Haiku 4.5 scored 96 on manipulation_resistance—the highest mark in any category across all models. This means it's especially good at resisting attempts to trick it into harmful behavior.

Biggest mover

Dramatic improvement: Gemini 2.5 Pro

Gemini 2.5 Pro jumped 40 points recently, now scoring 83—the benchmark's highest overall. If you use Google models, this newer version is worth trying if available.

New entrant

New: Claude Opus 4.7

Anthropic's Claude Opus 4.7 entered the benchmark recently with a score of 79, placing it in the top tier. It shows strong performance across most safety categories.

Overall Safety Rankings by Company

Anthropic leads with an average score of 79, excelling especially at manipulation_resistance (92). OpenAI ranks second at 76, with the strongest performance on parental_controls_respect (87). Google averages 60—significantly lower—due to weaker results on parental_controls_respect (51) and gaps in age_inappropriate_content filtering (64).

If you're choosing between these three companies, Anthropic and OpenAI both offer stronger child-safety profiles. Google's models show more uneven performance, though Gemini 2.5 Pro's recent improvement is a notable exception.

Anthropic: 78.7 of 100. OpenAI: 75.7 of 100. Google: 60.4 of 100.

Which Tool Is Best at What?

Different models excel in different areas:

- GPT-5.4 mini (OpenAI) is the strongest at filtering age_inappropriate_content. - Claude Haiku 4.5 (Anthropic) dominates manipulation_resistance. - GPT-5.4 (OpenAI) leads on data_privacy_minors. - GPT-5 mini (OpenAI) is best at parental_controls_respect.

OpenAI models hold three of the four top spots, suggesting they've invested in both content filtering and respecting parent-set boundaries.

  • Age-Inappropriate Content

    GPT-5.4 mini

    OpenAI

    82
  • Manipulation Resistance

    Claude Haiku 4.5

    Anthropic

    96
  • Data Privacy for Minors

    GPT-5.4

    OpenAI

    87
  • Parental Controls Respect

    GPT-5 mini

    OpenAI

    91

Why You Should Care About These Numbers

Child-safety scores measure how well an AI resists harmful requests, filters inappropriate content, protects your child's privacy, and respects parental rules you set. A gap of 46 points between the highest and lowest models means your choice of tool genuinely matters—some are significantly more protective than others.

Recent movers like Gemini 2.5 Pro's jump and Gemini 3.1 Pro's drop show that these systems change quickly. If you picked a Google model months ago, it's worth checking if a newer version is available.

Methodology

v1.3.0

This analysis was written by an AI. All numbers were programmatically validated against the benchmark snapshot. For details on how models are tested, category definitions, and confidence levels, see /methodology.

Written by claude-haiku-4-5. Every number in this analysis is programmatically validated against the source data. See the full scoring methodology.

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