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Nearmap AI Gen 6 vs Claude Fable and Gemini

In the 72 hours that Claude Fable was available, we benchmarked it against Nearmap AI. Here are the results.

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As general-purpose LLMs have matured, a fair question has emerged: do purpose-built AI models still hold a measurable advantage for defined property tasks? In June 2026, Nearmap ran a controlled benchmark comparing Nearmap AI Gen 6 against seven generalist models from Google and Anthropic, including Claude Fable 5. The test was run across four property intelligence tasks, including pool detection, roof area, roof count and roof condition.

Nearmap AI vs. Gemini Whitepaper
Nearmap AI Data Layers gif of US swimming pool detections

The benchmark

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hand-labelled US residential properties in the test dataset

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F1 score achieved by Nearmap AI Gen 6 on pool detection

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properties per second: Nearmap AI Gen 6 throughput

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generalist models tested across Google and Anthropic, including Fable
AI Accuracy

The results

Findings indicate a material performance gap across accuracy, failure mode distribution, and operational throughput, with structural causes that are unlikely to be resolved by improvements in general model capability alone.