Developer Tools / Code Assistant

Can AI draw San Francisco from memory? Six LLMs, scored against OpenStreetMap

A GitHub repo for a geospatial benchmark that tests how well six LLMs can classify points in San Francisco from memory and compares results against OpenStreetMap. It includes code, answers, answer keys, costs, and figures for reproducing the analysis.

Clear27/30
Useful24/30
Specific18/20
Complete10/20
Can AI draw San Francisco from memory? Six LLMs, scored against OpenStreetMap screenshot

Why it was accepted

The page clearly describes a real AI-related project with a specific use case: benchmarking LLM geographic knowledge against OpenStreetMap. The repository includes visible code, data/results folders, a README with methodology, model comparisons, and reproducible commands, which is enough for a useful public listing.

Weakness

The snapshot shows the project goal and top-line results, but not the full implementation details, exact model access requirements, or how the scoring pipeline is structured beyond the README text.

Review status

7 days ago #2068 ↑ +2

Last evaluated 7 days ago. Current rank #2068. Up 2 spots in the rankings.

Score history

79

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