multimodal benchmark
Vibe-Eval Leaderboard
VIBE-Eval is a hard evaluation suite for measuring progress of multimodal language models, consisting of 269 visual understanding prompts with gold-standard responses authored by experts. The benchmark has dual objectives: vibe checking multimodal chat models for day-to-day tasks and rigorously testing frontier models, with the hard set containing >50% questions that all frontier models answer incorrectly.
Updated Aug 17, 2026
Models8
Model coverage8
MetricScore
EvidenceB
Vibe-Eval Ranking
Higher score ranks better on this benchmark.
Sort by
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelGO | Score67.2% | Percentile100.0% | Participants8 | EvidenceC | Evaluated |
| Rank02 | ModelGO | Score65.6% | Percentile85.7% | Participants8 | EvidenceC | Evaluated |
| Rank03 | ModelGO | Score65.4% | Percentile71.4% | Participants8 | EvidenceC | Evaluated |
| Rank04 | ModelGO | Score56.3% | Percentile57.1% | Participants8 | EvidenceC | Evaluated |
| Rank05 | ModelGO | Score53.9% | Percentile42.9% | Participants8 | EvidenceC | Evaluated |
| Rank06 | ModelGO | Score51.3% | Percentile28.6% | Participants8 | EvidenceC | Evaluated |
| Rank07 | ModelGO | Score48.9% | Percentile14.3% | Participants8 | EvidenceC | Evaluated |
| Rank08 | ModelGO | Score40.9% | Percentile0.0% | Participants8 | EvidenceC | Evaluated |
Vibe-Eval Highlights
The leading models and scores on this benchmark.
Vibe-Eval Score Distribution
A closer view of the leading scores on this benchmark.
The Top AI Models for Vibe-Eval
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
Ranking basisThis vibe-eval AI model leaderboard uses descending score in the benchmark's original unit. The leaderboard ranking keeps matched price and speed data separate from benchmark evidence.
- 01GO
- Score
- 67.2%
- Price
- $1.3 input / $10 output per 1M tokens
- Speed
- Up to 85 tok/s via Google
Strengths
- Ranks #1 of 8 compared models
- 100th percentile on this benchmark
- C evidence result
Considerations
- This result measures Vibe-Eval, not total model capability
- 02GOGemini 2.5 ProGoogle
- Score
- 65.6%
- Price
- $1.3 input / $10 output per 1M tokens
- Speed
- Up to 86 tok/s via Google
Strengths
- Ranks #2 of 8 compared models
- 86th percentile on this benchmark
- C evidence result
Considerations
- This result measures Vibe-Eval, not total model capability
- 03GOGemini 2.5 FlashGoogle
- Score
- 65.4%
- Price
- $0.30 input / $2.5 output per 1M tokens
- Speed
- Up to 85 tok/s via Google
Strengths
- Ranks #3 of 8 compared models
- 71th percentile on this benchmark
- C evidence result
Considerations
- This result measures Vibe-Eval, not total model capability
- 04GOGemini 2.0 FlashGoogle
- Score
- 56.3%
- Speed
- Up to 183 tok/s via Google
Strengths
- Ranks #4 of 8 compared models
- 57th percentile on this benchmark
- C evidence result
Considerations
- This result measures Vibe-Eval, not total model capability
- 05GOGemini 1.5 ProGoogle
- Score
- 53.9%
- Speed
- Up to 85 tok/s via Google
Strengths
- Ranks #5 of 8 compared models
- 43th percentile on this benchmark
- C evidence result
Considerations
- This result measures Vibe-Eval, not total model capability
Selection summary
Best AI Models for Vibe-Eval
Gemini 2.5 Pro Preview 06-05 currently leads Vibe-Eval with 67.2%. 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.
What is Vibe-Eval?
What Vibe-Eval measures and how its scores work.
VIBE-Eval is a hard evaluation suite for measuring progress of multimodal language models, consisting of 269 visual understanding prompts with gold-standard responses authored by experts. The benchmark has dual objectives: vibe checking multimodal chat models for day-to-day tasks and rigorously testing frontier models, with the hard set containing >50% questions that all frontier models answer incorrectly.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- Vibe-Eval
- Modality
- multimodal
- Primary category
- multimodal
- Score direction
- higher
- LLMBoard eligible
- Yes
- Evaluation key
- vibe-eval|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about Vibe-Eval.
Which model scores highest on Vibe-Eval?
Gemini 2.5 Pro Preview 06-05 is currently ranked first with 67.2%.
What does Vibe-Eval measure?
VIBE-Eval is a hard evaluation suite for measuring progress of multimodal language models, consisting of 269 visual understanding prompts with gold-standard responses authored by experts. The benchmark has dual objectives: vibe checking multimodal chat models for day-to-day tasks and rigorously testing frontier models, with the hard set containing >50% questions that all frontier models answer incorrectly.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
8 model results are currently shown.
Does this benchmark affect the overall score?
Yes. This benchmark can contribute to the current LLMBoard capability score.