RISEBrowse 284 families
RISE
Can the model plan, use tools, and finish a multi-step task?
Version / measure
- Domain
- Agents
- Ranked models
- 6
- Reported values
- 6
- Reports
- 1 · lab
- Direction
- Higher is better
- Status
- Version not specified
Rankings
Best reported score per model across effort settings
| # | Model | Best setting | Score |
|---|---|---|---|
| 1 | Claude Opus 4.6Anthropic | reportedcost n/a1 value · Feb 12 · source | 62.5% |
| 2 | Claude Opus 4.5Anthropic | reportedcost n/a1 value · Feb 12 · source | 50.5% |
| 3 | MiniMax M2.5MiniMaxOW | reportedcost n/a1 value · Feb 12 · source | 50.2% |
| 4 | GPT-5.2OpenAI | reportedcost n/a1 value · Feb 12 · source | 50.0% |
| 5 | Gemini 3 ProGoogle | reportedcost n/a1 value · Feb 12 · source | 36.8% |
| 6 | MiniMax M2.1MiniMaxOW | reportedcost n/a1 value · Feb 12 · source | 34.0% |
Effort curve
Score vs. reported cost. Lines connect complete sweeps only.
No cost-linked effort sweep for this version.
Definition and comparison boundaryinternal methodology
Can the model plan, use tools, and finish a multi-step task?
Agentic execution across tools, environments, or long-running workflows. Higher is better. The value is the percentage reported in this lab's table.
This is a publisher-defined internal evaluation. The task set or grading details are not fully public, so treat it as directional evidence.
Method / source ↗