multimodal benchmark
MM-MT-Bench
A multi-turn LLM-as-a-judge evaluation benchmark for testing multimodal instruction-tuned models' ability to follow user instructions in multi-turn dialogues and answer open-ended questions in a zero-shot manner.
Updated Aug 7, 2026
Published models17
Registry coverage17
MetricScore
EvidenceB
MM-MT-Bench leaderboard
Sorted by the source-provided rank. Higher score is better according to the registry.
Score distribution
Top published rows on the benchmark's original scale.
MM-MT-Bench highlights
The top published results on this benchmark's own scale.
What is MM-MT-Bench?
Definition and scoring fields from the benchmark registry.
A multi-turn LLM-as-a-judge evaluation benchmark for testing multimodal instruction-tuned models' ability to follow user instructions in multi-turn dialogues and answer open-ended questions in a zero-shot manner.
Scores are shown in points. The current registry marks this benchmark as not independently verified with evidence level B.
- Family
- MM-MT-Bench
- Modality
- multimodal
- Primary category
- multimodal
- Score direction
- higher
- LLMBoard eligible
- No
- Evaluation key
- mm-mt-bench|llm-stats-current
Source-native results are preserved. Eligibility for the overall LLMBoard score is a separate policy decision.
FAQ
Common questions about MM-MT-Bench.
Which model scores highest on MM-MT-Bench?
Mistral Large 3 is currently ranked first with 84.9 points.
What does MM-MT-Bench measure?
A multi-turn LLM-as-a-judge evaluation benchmark for testing multimodal instruction-tuned models' ability to follow user instructions in multi-turn dialogues and answer open-ended questions in a zero-shot manner.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
17 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.