multimodal benchmark
MuirBench is a multimodal benchmark for evaluating multi-image understanding across 12 tasks covering 10 categories of multi-image relations.
Updated Sep 5, 2026
Higher score ranks better on this benchmark.
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelAC | Score80.30% | Percentile100.00% | Participants12 | EvidenceC | Evaluated |
| Rank02 | ModelAC | Score80.10% | Percentile90.91% | Participants12 | EvidenceC | Evaluated |
| Rank03 | ModelAC | Score77.60% | Percentile81.82% | Participants12 | EvidenceC | Evaluated |
| Rank04 | ModelAC | Score76.80% | Percentile72.73% | Participants12 | EvidenceC | Evaluated |
| Rank05 | ModelAC | Score75.00% | Percentile63.64% | Participants12 | EvidenceC | Evaluated |
| Rank06 | ModelAC | Score72.80% | Percentile54.55% | Participants12 | EvidenceC | Evaluated |
| Rank07 | ModelAC | Score72.80% | Percentile45.45% | Participants12 | EvidenceC | Evaluated |
| Rank08 | ModelAC | Score64.40% | Percentile36.36% | Participants12 | EvidenceC | Evaluated |
| Rank09 | ModelAC | Score63.80% | Percentile27.27% | Participants12 | EvidenceC | Evaluated |
| Rank10 | ModelAC | Score62.90% | Percentile18.18% | Participants12 | EvidenceC | Evaluated |
| Rank11 | ModelAC | Score59.20% | Percentile9.09% | Participants12 | EvidenceC | Evaluated |
| Rank12 | ModelLA | Score58.30% | Percentile0.00% | Participants12 | 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 MuirBench measures and how its scores work.
MuirBench consists of 11,264 images and 2,600 multiple-choice questions created in a pairwise manner, with each standard instance paired with an unanswerable variant.
It measures multi-image understanding capabilities using the Score metric, reported as a ratio.
Scores are shown in ratio. 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 MuirBench.
Qwen3 VL 32B Thinking is currently ranked first with 80.30%.
The current leaders are Qwen3 VL 32B Thinking (80.30%), Qwen3 VL 235B A22B Thinking (80.10%), and Qwen3 VL 30B A3B Thinking (77.60%).
Qwen2.5-Omni-7B has the lowest matched official input price at $0.10 input / $0.40 output per 1M tokens.
The fastest matched records are Qwen3 VL 4B Thinking (8.77 tok/s via DeepInfra).
No. This benchmark measures one defined capability or task. The overall LLMBoard score uses a separate aggregation across eligible benchmark evidence.
It measures multi-image understanding capabilities using the Score metric, reported as a ratio.
Yes. Higher values rank better for this benchmark.
12 model results are currently shown.
No. This benchmark is shown for reference but does not contribute to the overall score.
Ranking basisThis muirbench 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
Qwen3 VL 32B Thinking currently leads MuirBench with 80.30%. 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.