agents benchmark
Claw-Eval
Claw-Eval tests real-world agentic task completion across complex multi-step scenarios, evaluating a model's ability to use tools, navigate environments, and complete end-to-end tasks autonomously.
Updated Aug 11, 2026
Models13
Model coverage13
MetricScore
EvidenceB
Claw-Eval Ranking
Higher score ranks better on this benchmark.
| 01 | MA | 80.9% | 100.0% | 13 | C | |
| 02 | ZA | 75.0% | 91.7% | 13 | C | |
| 03 | MI | 74.5% | 83.3% | 13 | C | |
| 04 | TE | 68.5% | 75.0% | 13 | C | |
| 05 | AC | 65.2% | 66.7% | 13 | C | |
| 06 | XI | 64.0% | 58.3% | 13 | C | |
| 07 | XI | 63.2% | 50.0% | 13 | C | |
| 08 | AC | 62.7% | 41.7% | 13 | C | |
| 09 | XI | 61.5% | 33.3% | 13 | C | |
| 10 | AC | 60.6% | 25.0% | 13 | C | |
| 11 | AC | 58.7% | 16.7% | 13 | C | |
| 12 | XI | 54.8% | 8.3% | 13 | C | |
| 13 | AC | 50.0% | 0.0% | 13 | C |
Claw-Eval Score Distribution
A closer view of the leading scores on this benchmark.
Claw-Eval Highlights
The leading models and scores on this benchmark.
What is Claw-Eval?
What Claw-Eval measures and how its scores work.
Claw-Eval tests real-world agentic task completion across complex multi-step scenarios, evaluating a model's ability to use tools, navigate environments, and complete end-to-end tasks autonomously.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- Claw-Eval
- Modality
- text
- Primary category
- agents
- Score direction
- higher
- LLMBoard eligible
- Yes
- Evaluation key
- claw-eval|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about Claw-Eval.
Which model scores highest on Claw-Eval?
Kimi K2.6 is currently ranked first with 80.9%.
What does Claw-Eval measure?
Claw-Eval tests real-world agentic task completion across complex multi-step scenarios, evaluating a model's ability to use tools, navigate environments, and complete end-to-end tasks autonomously.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
13 model results are currently shown.
Does this benchmark affect the overall score?
Yes. This benchmark can contribute to the current LLMBoard capability score.