MM-IFEval

MM-IFEval is a benchmark for how precisely a model obeys the instructions it was given. The official description says: "MM-IFEval as evaluated on the LFM3-VL-2B card (vision benchmark, with-thinking setting): General category, with-thinking column". Below we describe in simple words what benchmarks of this type generally examine.

MM-IFEval measures how precisely a model obeys the instructions it was given. In detail, it checks:

• meeting verifiable constraints (length, format, language, layout)
• following several constraints correctly at once
• keeping the constraints over long, multi-turn conversations
• not ignoring parts of the instruction while sounding plausible

The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better.

Official methodology note: MM-IFEval as evaluated on the LFM3-VL-2B card (vision benchmark, with-thinking setting): General category, with-thinking column. Multimodal instruction following; distinct from the text-only 'IFEval' and 'Multi-IF' records in the inventory.

What is the MM-IFEval benchmark?

MM-IFEval is a benchmark for how precisely a model obeys the instructions it was given. The official description says: 'MM-IFEval as evaluated on the LFM3-VL-2B card (vision benchmark, with-thinking setting): General category, with-thinking column'. Below we describe in simple words what benchmarks of this type generally examine.

What does MM-IFEval test?

MM-IFEval mainly measures how precisely a model obeys the instructions it was given. Concretely, it checks: meeting verifiable constraints (length, format, language, layout); following several constraints correctly at once; keeping the constraints over long, multi-turn conversations.

How is the MM-IFEval score calculated?

The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better. The declared maximum score of this benchmark is 100.0.

Where do I get MM-IFEval data and scores?

The official benchmark page/reference is linked on this page. Every score on Open LLM Radar is also available as open data: download the scores JSON (http://open-llm-radar-api:8000/api/v1/benchmarks/mm-ifeval/scores) or pull it directly from the Open LLM Radar API with any HTTP client.