reasoning benchmark
ACEBench
ACEBench is a comprehensive benchmark for evaluating Large Language Models' tool usage capabilities across three primary evaluation types: Normal (basic tool usage scenarios), Special (tool usage with ambiguous or incomplete instructions), and Agent (multi-agent interactions simulating real-world dialogues). The benchmark covers 4,538 APIs across 8 major domains and 68 sub-domains including technology, finance, entertainment, society, health, culture, and environment, supporting both English and Chinese languages.
Updated Aug 7, 2026
Published models2
Registry coverage2
MetricScore
EvidenceB
ACEBench leaderboard
Sorted by the source-provided rank. Higher score is better according to the registry.
| 1 | MA | 76.5% | 100.0% | 2 | C | |
| 2 | MA | 76.5% | 0.0% | 2 | C |
Score distribution
Top published rows on the benchmark's original scale.
ACEBench highlights
The top published results on this benchmark's own scale.
What is ACEBench?
Definition and scoring fields from the benchmark registry.
ACEBench is a comprehensive benchmark for evaluating Large Language Models' tool usage capabilities across three primary evaluation types: Normal (basic tool usage scenarios), Special (tool usage with ambiguous or incomplete instructions), and Agent (multi-agent interactions simulating real-world dialogues). The benchmark covers 4,538 APIs across 8 major domains and 68 sub-domains including technology, finance, entertainment, society, health, culture, and environment, supporting both English and Chinese languages.
Scores are shown in ratio. The current registry marks this benchmark as not independently verified with evidence level B.
- Family
- ACEBench
- Modality
- text
- Primary category
- reasoning
- Score direction
- higher
- LLMBoard eligible
- No
- Evaluation key
- acebench|llm-stats-current
Source-native results are preserved. Eligibility for the overall LLMBoard score is a separate policy decision.
FAQ
Common questions about ACEBench.
Which model scores highest on ACEBench?
Kimi K2 Instruct is currently ranked first with 76.5%.
What does ACEBench measure?
ACEBench is a comprehensive benchmark for evaluating Large Language Models' tool usage capabilities across three primary evaluation types: Normal (basic tool usage scenarios), Special (tool usage with ambiguous or incomplete instructions), and Agent (multi-agent interactions simulating real-world dialogues). The benchmark covers 4,538 APIs across 8 major domains and 68 sub-domains including technology, finance, entertainment, society, health, culture, and environment, supporting both English and Chinese languages.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
2 unique published model results are currently shown.
Does this benchmark affect the overall score?
This benchmark is preserved as source-native evidence but is not eligible for the current overall score.