Tool Decathlon
Tool Decathlon - agentic tool use benchmark.
Category
General Agents
Score type
percent
Scale
100%
higher is better
Models tested
7
What is Tool Decathlon?
Tool Decathlon is a benchmark for how well a model acts as a general-purpose agent. The official description says: "Tool Decathlon - agentic tool use benchmark". Below we describe in simple words what benchmarks of this type generally examine.
What does it test?
Tool Decathlon measures how well a model acts as a general-purpose agent. In detail, it checks:
- solving long, multi-step tasks with many intermediate decisions
- using tools correctly (browsers, terminals, APIs, calendars, other apps)
- adapting when something unexpected happens mid-task
- staying on goal over long task horizons instead of wandering off
How to read the score
The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better.
Official methodology note: Tool Decathlon - agentic tool use benchmark.
Frequently asked questions
What is the Tool Decathlon benchmark?
Tool Decathlon is a benchmark for how well a model acts as a general-purpose agent. The official description says: 'Tool Decathlon - agentic tool use benchmark'. Below we describe in simple words what benchmarks of this type generally examine.
What does Tool Decathlon test?
Tool Decathlon mainly measures how well a model acts as a general-purpose agent. Concretely, it checks: solving long, multi-step tasks with many intermediate decisions; using tools correctly (browsers, terminals, APIs, calendars, other apps); adapting when something unexpected happens mid-task.
How is the Tool Decathlon score calculated?
The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better. The declared maximum score of this benchmark is 100.0.
Where do I get Tool Decathlon data and scores?
The official benchmark page/reference is linked on this page. Every score on Open LLM Radar is also available as open data: download the scores JSON (http://open-llm-radar-api:8000/api/v1/benchmarks/tool-decathlon/scores) or pull it directly from the Open LLM Radar API with any HTTP client.
Benchmark data & downloads
Where to get, inspect and reuse the data behind this benchmark.
Model scores 7 models tested
| # | Model | Score | Date | Source | Verified |
|---|---|---|---|---|---|
| 1 |
DeepSeek-V4-Pro
DeepSeek
|
52.8%
|
17.06.2026 | Report | Unverified |
| 2 |
GLM-5.2
Zhipu AI
|
48.2%
|
17.06.2026 | Report | Verified |
| 3 |
Qwen3.5-27B
Qwen Team (Alibaba Cloud)
|
31.5%
|
16.04.2026 | Qwen Team (official model card - comparison) | Unverified |
| 4 |
Qwen3.5-35B-A3B
Qwen Team (Alibaba Cloud)
|
28.7%
|
16.04.2026 | Qwen Team (official model card - comparison) | Unverified |
| 5 |
Qwen3.6-35B-A3B
Qwen Team (Alibaba Cloud)
|
26.9%
|
16.04.2026 | Qwen Team (official model card) | Verified |
| 6 |
Gemma4-31B-it
Google
|
21.2%
|
16.04.2026 | Qwen Team (official model card - comparison) | Unverified |
| 7 |
Gemma4-26B-A4B
Google
|
12%
|
16.04.2026 | Qwen Team (official model card - comparison) | Unverified |