reasoning benchmark
ARC-AGI v2
ARC-AGI-2 is an upgraded benchmark for measuring abstract reasoning and problem-solving abilities in AI systems through visual grid transformation tasks. It evaluates fluid intelligence via input-output grid pairs (1x1 to 30x30) using colored cells (0-9), requiring models to identify underlying transformation rules from demonstration examples and apply them to test cases. Designed to be easy for humans but challenging for AI, focusing on core cognitive abilities like spatial reasoning, pattern recognition, and compositional generalization.
Updated Aug 11, 2026
Models16
Model coverage16
MetricScore
EvidenceB
ARC-AGI v2 Ranking
Higher score ranks better on this benchmark.
| 01 | OP | 85.0% | 100.0% | 16 | C | |
| 02 | GO | 77.1% | 93.3% | 16 | C | |
| 03 | OP | 73.3% | 86.7% | 16 | C | |
| 04 | GO | 72.1% | 80.0% | 16 | C | |
| 05 | AN | 68.8% | 73.3% | 16 | C | |
| 06 | AN | 58.3% | 66.7% | 16 | C | |
| 07 | OP | 54.2% | 60.0% | 16 | C | |
| 08 | OP | 52.9% | 53.3% | 16 | C | |
| 09 | ME | 42.5% | 46.7% | 16 | C | |
| 10 | AN | 37.6% | 40.0% | 16 | C | |
| 11 | GO | 33.6% | 33.3% | 16 | C | |
| 12 | GO | 31.1% | 26.7% | 16 | C | |
| 13 | XA | 15.9% | 20.0% | 16 | C | |
| 14 | AN | 8.6% | 13.3% | 16 | B | |
| 15 | OP | 6.5% | 6.7% | 16 | B | |
| 16 | GO | 4.9% | 0.0% | 16 | B |
ARC-AGI v2 Score Distribution
A closer view of the leading scores on this benchmark.
ARC-AGI v2 Highlights
The leading models and scores on this benchmark.
What is ARC-AGI v2?
What ARC-AGI v2 measures and how its scores work.
ARC-AGI-2 is an upgraded benchmark for measuring abstract reasoning and problem-solving abilities in AI systems through visual grid transformation tasks. It evaluates fluid intelligence via input-output grid pairs (1x1 to 30x30) using colored cells (0-9), requiring models to identify underlying transformation rules from demonstration examples and apply them to test cases. Designed to be easy for humans but challenging for AI, focusing on core cognitive abilities like spatial reasoning, pattern recognition, and compositional generalization.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- ARC-AGI v2
- Modality
- multimodal
- Primary category
- reasoning
- Score direction
- higher
- LLMBoard eligible
- Yes
- Evaluation key
- arc-agi-v2|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about ARC-AGI v2.
Which model scores highest on ARC-AGI v2?
GPT-5.5 is currently ranked first with 85.0%.
What does ARC-AGI v2 measure?
ARC-AGI-2 is an upgraded benchmark for measuring abstract reasoning and problem-solving abilities in AI systems through visual grid transformation tasks. It evaluates fluid intelligence via input-output grid pairs (1x1 to 30x30) using colored cells (0-9), requiring models to identify underlying transformation rules from demonstration examples and apply them to test cases. Designed to be easy for humans but challenging for AI, focusing on core cognitive abilities like spatial reasoning, pattern recognition, and compositional generalization.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
16 model results are currently shown.
Does this benchmark affect the overall score?
Yes. This benchmark can contribute to the current LLMBoard capability score.