reasoning benchmark
Seal-0
Seal-0 is a benchmark for evaluating agentic search capabilities, testing models' ability to navigate and retrieve information using tools.
Updated Aug 11, 2026
Models6
Model coverage6
MetricScore
EvidenceB
Seal-0 Ranking
Higher score ranks better on this benchmark.
| 1 | MA | 57.4% | 100.0% | 6 | C | |
| 2 | MA | 56.3% | 80.0% | 6 | C | |
| 3 | AC | 47.2% | 60.0% | 6 | C | |
| 4 | AC | 46.9% | 40.0% | 6 | C | |
| 5 | AC | 44.1% | 20.0% | 6 | C | |
| 6 | AC | 41.4% | 0.0% | 6 | C |
Seal-0 Score Distribution
A closer view of the leading scores on this benchmark.
Seal-0 Highlights
The leading models and scores on this benchmark.
What is Seal-0?
What Seal-0 measures and how its scores work.
Seal-0 is a benchmark for evaluating agentic search capabilities, testing models' ability to navigate and retrieve information using tools.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- Seal-0
- Modality
- text
- Primary category
- reasoning
- Score direction
- higher
- LLMBoard eligible
- Yes
- Evaluation key
- seal-0|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about Seal-0.
Which model scores highest on Seal-0?
Kimi K2.5 is currently ranked first with 57.4%.
What does Seal-0 measure?
Seal-0 is a benchmark for evaluating agentic search capabilities, testing models' ability to navigate and retrieve information using tools.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
6 model results are currently shown.
Does this benchmark affect the overall score?
Yes. This benchmark can contribute to the current LLMBoard capability score.