MMSearch
We show this table for reference; we do not rank on it.
A multimodal search benchmark for retrieval and grounded answering across mixed-media inputs.
About MMSearch
Year
2026
Tasks
Multimodal search tasks
Format
Mixed-media retrieval and grounded answering
Difficulty
Multimodal search
BenchLM stores MMSearch as a display-only benchmark because it is not yet part of the weighted core schema.
Freshness and provenance
Version
MMSearch 2026
Refresh cadence
Quarterly
Staleness state
Current
Question availability
Public benchmark set
BenchLM uses freshness metadata to decide whether a benchmark should still be treated as a strong differentiator, a benchmark to watch, or a display-only reference. For the full scoring policy, see the BenchLM methodology page.
Questions
What does MMSearch measure?
A multimodal search benchmark for retrieval and grounded answering across mixed-media inputs.
Which model scores highest on MMSearch?
No sourced model results are published for MMSearch on BenchLM yet.
How many models are evaluated on MMSearch?
0 AI models have published results on MMSearch in the BenchLM catalog.
Know when it’s worth switching models
The model to choose, the cheaper alternative, and the release we would wait on.
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