ChildAgentEval: leaderboard
While agentic AI and its core multimodal large language models (MLLMs) have demonstrated remarkable promise in language and visual reasoning across domains ranging from daily life to advanced scientific research, a profound gap remains between artificial and human intelligence. Despite the integration of powerful tools and advanced MLLMs, state-of-the-art AI agents frequently fail at foundational,
Metric: Total (self-reported). Source: benchmarklist.com. Saturation forecast: Around September 2027. 6 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | GPT-5.4 | 53 | #79 |
| 2 | Gemini 3.1 Pro (Preview) | 48 | #58 |
| 3 | Gemini 3.1 Flash Lite | 48 | #191 |
| 4 | Qwen 3.6 Plus | 37 | #120 |
| 5 | Qwen 3.5 27B | 34 | #187 |
| 6 | Gemma 4 31B (IT) | 29 | #176 |
No result here: #3 Claude Opus 5.5, #6 GPT-6 Astra, #7 GPT-6.1 Sol.
Interactive version: theaggregate.ai/benchmark?slug=childagenteval · How It Works · Data refreshed daily, snapshot 2026-10-20.