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Geocoding benchmarks: geolith, Nominatim, Photon, Pelias

geolith, Nominatim, Photon and Pelias ran in Docker on the same machine with the same India data (20 Oct 2026), 200 queries per set. geolith had the best top-1 on 5 of 7 sets: 95.0 % on OSM addresses, 82.5 % on autocomplete, 93.0 % on Overture POIs. Photon leads on OSM POIs and Nominatim on reverse.

India · top-1 %

Accuracy per query set

India top-1 accuracy by engine
Set geolith NominatimPhotonPelias
OSM places95.085.080.577.0
OSM addresses95.050.588.561.5
OSM POIs84.568.585.561.0
Overture POIs93.06.012.57.0
Autocomplete82.5n/a42.532.5
Near a point96.044.552.039.0
Reverse99.5100.098.598.0
Feature probes (of 25) 24211916

Top-1 accuracy (%), 200 queries per set. All four engines in Docker on the same India data, 20 Oct 2026. Best per row in teal. Nominatim has no autocomplete endpoint. Method and raw results.

Detail

How a result counts

A result counts when it lies within the gold radius of the gold point. Feature probes (25 single-capability queries): geolith 24, Nominatim 21, Photon 19, Pelias 16.

Detail

The whole world in one file

Planet file (22 Oct 2026): 31.63 GB, 678,043,458 places, built in 5 h 28 min. It answered 21/21 world test queries; the slowest took 110 ms on a warm local server.

Detail

How often the first result matches Google's

On 194 real India queries, geolith's first result was within 1 km of Google's for 113 (58 %). We do not claim geolith is better than Google.

Detail

Full reports

The docs have the conditions, every table and the commands to reproduce the runs.

  • Engines: accuracy, feature probes, latency, load and disk (https://docs.geolith.app/search/benchmarks/engines).
  • Latency of the .glx file read from local disk (https://docs.geolith.app/search/benchmarks/latency).
  • Reading a town without a comma, such as "mg road pune" (https://docs.geolith.app/search/benchmarks/town-reading).

Sources

  1. geolith search benchmarks: engines, geolith (read 2026-10-22)

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