Google DeepMind's new benchmark tests agents on blueprints, schematics and polished decks
Built with Artificial Analysis, MKA uses 200 expert-designed tasks to grade visual knowledge work. Google says Gemini 4 Carbon ranks second on quality at a lower cost.
By RuntimeWire Staff · Published · Updated
Primary source: Google Gemini (official)
Why it matters
MKA evaluates agents on visual files and finished deliverables that define professional work. For model buyers, Google's second-place quality ranking paired with a claimed sixfold cost advantage makes price per completed task a number to compare alongside peak score.
Google DeepMind senior product manager Rohan Doshi and research director Ben Caine launched the Multimodal Knowledge Agent benchmark on November 10th, a 200-task test built with Artificial Analysis to grade how AI agents handle visually dense professional files. Google says Gemini 4 Carbon ranks second on quality in the test while completing tasks at six times lower cost on average than the top-scoring model.…
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