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fontbench

fontbench tests whether vision models can identify a typeface from a rendered image. Each item shows one specimen and four candidate font families; the model picks one.

Latest run

Accuracy

Accuracy leaderboard

Cost

Cost leaderboard

Speed

Speed leaderboard

Results are from 60 items (three seeded runs of 20) on the private mixed dataset. Runs use the Cursor SDK, so token counts are a cost proxy rather than provider API prices. See the live benchmark for methodology and context.

Reproduce

Requires Bun.

bun install
bun run dataset:all
bun run e2b:eval -- --model gemini-3.1-pro --limit 20

See DATASET.md for dataset and evaluation details.

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A vision model eval and benchmark for identifying typefaces from rendered images, comparing accuracy, cost, and speed.

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