multimodal benchmark
Meld Leaderboard
MELD (Multimodal EmotionLines Dataset) is a multimodal multi-party dataset for emotion recognition in conversations. Contains approximately 13,000 utterances from 1,433 dialogues extracted from the TV series Friends. Each utterance is annotated with emotion (Anger, Disgust, Sadness, Joy, Neutral, Surprise, Fear) and sentiment labels across audio, visual, and textual modalities.
Updated Aug 17, 2026
Models1
Model coverage1
MetricScore
EvidenceB
Meld Ranking
Higher score ranks better on this benchmark.
Sort by
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelAC | Score57.0% | Percentile100.0% | Participants1 | EvidenceC | Evaluated |
Meld Highlights
The leading models and scores on this benchmark.
The Top AI Models for Meld
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
Ranking basisThis meld 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.
- 01ACQwen2.5-Omni-7BAlibaba Cloud / Qwen Team
- Score
- 57.0%
- Price
- $0.10 input / $0.40 output per 1M tokens
Strengths
- Ranks #1 of 1 compared models
- 100th percentile on this benchmark
- C evidence result
Considerations
- This result measures Meld, not total model capability
Selection summary
Best AI Models for Meld
Qwen2.5-Omni-7B currently leads Meld with 57.0%. 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 Meld?
What Meld measures and how its scores work.
MELD (Multimodal EmotionLines Dataset) is a multimodal multi-party dataset for emotion recognition in conversations. Contains approximately 13,000 utterances from 1,433 dialogues extracted from the TV series Friends. Each utterance is annotated with emotion (Anger, Disgust, Sadness, Joy, Neutral, Surprise, Fear) and sentiment labels across audio, visual, and textual modalities.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- Meld
- Modality
- multimodal
- Primary category
- multimodal
- Score direction
- higher
- LLMBoard eligible
- No
- Evaluation key
- meld|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about Meld.
Which model scores highest on Meld?
Qwen2.5-Omni-7B is currently ranked first with 57.0%.
What does Meld measure?
MELD (Multimodal EmotionLines Dataset) is a multimodal multi-party dataset for emotion recognition in conversations. Contains approximately 13,000 utterances from 1,433 dialogues extracted from the TV series Friends. Each utterance is annotated with emotion (Anger, Disgust, Sadness, Joy, Neutral, Surprise, Fear) and sentiment labels across audio, visual, and textual modalities.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
1 model results are currently shown.
Does this benchmark affect the overall score?
No. This benchmark is shown for reference but does not contribute to the overall score.