multimodal benchmark
ZEROBench is a multimodal vision benchmark for zero-shot visual understanding tasks.
Updated Sep 5, 2026
Higher score ranks better on this benchmark.
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelMA | Score0.41 points | Percentile100.00% | Participants10 | EvidenceC | Evaluated |
| Rank02 | ModelDE | Score0.35 points | Percentile88.89% | Participants10 | EvidenceC | Evaluated |
| Rank03 | ModelME | Score0.33 points | Percentile77.78% | Participants10 | EvidenceC | Evaluated |
| Rank04 | ModelBY | Score0.18 points | Percentile66.67% | Participants10 | EvidenceC | Evaluated |
| Rank05 | ModelMA | Score0.11 points | Percentile55.56% | Participants10 | EvidenceC | Evaluated |
| Rank06 | ModelBY | Score0.11 points | Percentile44.44% | Participants10 | EvidenceC | Evaluated |
| Rank07 | ModelAC | Score0.10 points | Percentile33.33% | Participants10 | EvidenceC | Evaluated |
| Rank08 | ModelAC | Score0.09 points | Percentile22.22% | Participants10 | EvidenceC | Evaluated |
| Rank09 | ModelAC | Score0.08 points | Percentile11.11% | Participants10 | EvidenceC | Evaluated |
| Rank10 | ModelAC | Score0.04 points | Percentile0.00% | Participants10 | EvidenceC | Evaluated |
The leading models and scores on this benchmark.
A closer view of the leading scores on this benchmark.
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
What ZEROBench measures and how its scores work.
ZEROBench is a vision benchmark designed to test models on zero-shot visual understanding tasks.
ZEROBench measures performance on zero-shot visual understanding tasks using a Score reported in points.
Scores are shown in points. This benchmark is not independently verified and has an evidence level of B.
LLM Stats. Benchmark scores retain their original unit. Overall score eligibility is shown separately.
Common questions about ZEROBench.
Kimi K3 is currently ranked first with 0.41 points.
The current leaders are Kimi K3 (0.41 points), DeepSeek-V4-Flash-Vision-Exp (0.35 points), and Muse Spark (0.33 points).
DeepSeek-V4-Flash-Vision-Exp has the lowest matched official input price at $0.14 input / $0.28 output per 1M tokens.
No matched runtime record is currently available.
No. This benchmark measures one defined capability or task. The overall LLMBoard score uses a separate aggregation across eligible benchmark evidence.
ZEROBench measures performance on zero-shot visual understanding tasks using a Score reported in points.
Yes. Higher values rank better for this benchmark.
10 model results are currently shown.
No. This benchmark is shown for reference but does not contribute to the overall score.
Ranking basisThis zerobench AI model leaderboard uses descending score in the benchmark original unit. The leaderboard ranking keeps matched price and speed data separate from benchmark evidence.
Selection summary
Kimi K3 currently leads ZEROBench with 0.41 points. It is the top model on this specific benchmark, while the best LLM for the broader task should also be checked against other benchmarks, price, and runtime.
Use this leaderboard with the supporting benchmark results and coverage details above. A leaderboard position summarizes the selected ranking signal; it does not replace workload-specific testing.