DTap-Bench (Benign Tasks) - Research: leaderboard
Benign research tasks from DTap-Bench (Chen et al., 2026), run by a tool-using agent in simulated MCP environments with no attack applied. Success rate in percent over 160 tasks, averaged over task categories and judged by a rule-based check of the final environment state; higher is better.
Metric: Benign task success rate (%; 160 benign research tasks, no attack applied; a task succeeds when a rule-based check of the final environment state finds the instruction fully completed; mean of its task-category rates). Source: arxiv.org. Saturation forecast: Estimated already saturated. 9 models tracked.
Top models
| # | Model | Score | Overall rank |
|---|---|---|---|
| 1 | Claude Sonnet 4.5 | 100 | #244 |
| 2 | Gemini 3 Pro | 100 | #135 |
| 3 | GPT-5.5 | 99 | #48 |
| 4 | DeepSeek V4 Pro | 96 | #181 |
| 5 | GPT-5.4 | 95 | #121 |
| 6 | GPT-5.2 | 94.5 | #172 |
| 7 | GPT-5.1 | 90 | #225 |
| 8 | GPT-OSS-120B | 30 | #699 |
No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.
Interactive version: theaggregate.ai/benchmark?slug=dtap-bench-benign-tasks-research · How It Works · Data refreshed daily, snapshot 2026-11-12.