MM IF-Eval

A challenging multimodal instruction-following benchmark that includes both compose-level constraints for output responses and perception-level constraints tied to input images, with comprehensive evaluation pipeline.

Pixtral-12B from Mistral AI currently leads the MM IF-Eval leaderboard with a score of 0.527 across 1 evaluated AI models.

Paper

Pixtral-12B leads with 52.7%.

Progress Over Time

Interactive timeline showing model performance evolution on MM IF-Eval

State-of-the-art frontier

Open

Proprietary

MM IF-Eval Leaderboard

1 models

				Context	Cost	License
1	Pixtral-12B Mistral AI		12B	—	—

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FAQ

Common questions about MM IF-Eval.

What is the MM IF-Eval benchmark?

What is the MM IF-Eval leaderboard?

The MM IF-Eval leaderboard ranks 1 AI models based on their performance on this benchmark. Currently, Pixtral-12B by Mistral AI leads with a score of 0.527. The average score across all models is 0.527.

What is the highest MM IF-Eval score?

The highest MM IF-Eval score is 0.527, achieved by Pixtral-12B from Mistral AI.

How many models are evaluated on MM IF-Eval?

1 models have been evaluated on the MM IF-Eval benchmark, with 0 verified results and 1 self-reported results.

Where can I find the MM IF-Eval paper?

The MM IF-Eval paper is available at https://arxiv.org/abs/2504.07957. The paper details the methodology, dataset construction, and evaluation criteria.

What categories does MM IF-Eval cover?

MM IF-Eval is categorized under multimodal, reasoning, and structured output. The benchmark evaluates multimodal models.

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