Best reverse geocoding API for mobile apps

Combined ranking

1. 1
   Google Maps Geocoding APIstore.google.com ↗—15 pts

   GPT #1Claude #1Gemini #1

   The safest default when address accuracy, global coverage, localization, place IDs, and dependable rooftop-level results matter most; especially strong for consumer apps already using Google Maps.

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   GPT The safest default when address accuracy, global coverage, localization, place IDs, and dependable rooftop-level results matter most; especially strong for consumer apps already using Google Maps.

   Claude Still the accuracy and coverage benchmark — rooftop-level results, best POI/address data in most countries, and native mobile SDKs plus the Android platform Geocoder; the 2024+ per-SKU pricing with monthly free tier makes moderate mobile volumes workable. Ranked first on the assumption the typical mobile app values correctness of the returned address above cost.

   Gemini Sets the global standard for rooftop-level geocoding accuracy and point-of-interest resolution, handling ambiguous or poorly formatted inputs better than any competitor.

   Where it falls short

   per GPT Expensive at scale, with restrictive caching, storage, attribution, and map-display terms.

   per Claude Expensive at scale (~$5/1k after credits) and its ToS forbid caching/storing results or displaying them on non-Google maps, which rules it out for apps that persist addresses or use Mapbox/OSM basemaps.

   per Gemini Extremely high cost combined with restrictive licensing terms that prohibit caching results beyond 30 days and mandate displaying results only on a Google Map.

2. 2
   MMapbox Geocoding API—10 pts

   GPT #2Claude #3Gemini #3

   Near-tied with Google for most mobile teams thanks to strong worldwide results, excellent iOS and Android integration, flexible map styling, structured address context, and substantially better entry-level value.

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   GPT Near-tied with Google for most mobile teams thanks to strong worldwide results, excellent iOS and Android integration, flexible map styling, structured address context, and substantially better entry-level value.

   Claude Strong mobile SDK integration (Maps + Search SDKs), competitive tiered pricing with a 100k free monthly tier, and a "permanent geocoding" option that legally allows storing results — a real differentiator over Google for apps that save user addresses.

   Gemini Delivers exceptional integration with highly customizable mobile mapping SDKs, featuring polished UI components and highly accurate street-level geocoding, nearly tying with Radar.

   Where it falls short

   per GPT Temporary-result storage restrictions and uneven address precision in some countries complicate data-heavy or archival use cases.

   per Claude Permanent geocoding costs several times the temporary rate, and reverse-geocode quality is a step below Google in address-sparse regions; you're also nudged into the Mapbox map ecosystem.

   per Gemini Becomes significantly less cost-effective at high scale unless tightly bound to Mapbox map views, and street data outside major urban centers can be less reliable.

3. 3
   RRadar—10 pts

   GPT #4Claude #2Gemini #2

   Built mobile-first — first-class iOS/Android SDKs, a 100k-calls/month free tier, and roughly 10x cheaper than Google beyond it ($0.50/1k range), with permissive terms that allow storing results; near-tie with Mapbox for the #2 spot, edged ahead on price and mobile SDK ergonomics.

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   Claude Built mobile-first — first-class iOS/Android SDKs, a 100k-calls/month free tier, and roughly 10x cheaper than Google beyond it ($0.50/1k range), with permissive terms that allow storing results; near-tie with Mapbox for the #2 spot, edged ahead on price and mobile SDK ergonomics.

   Gemini Offers a highly developer-friendly, mobile-optimized location platform acting as a drop-in replacement for Google Maps at up to 90% lower cost, nearly tying with Mapbox but edging it out on native mobile tracking and geofencing features.

   GPT The strongest mobile-first value choice, combining inexpensive reverse geocoding with polished iOS, Android, React Native, and Flutter tooling plus geofencing and location-fraud capabilities.

   Where it falls short

   per GPT Its geocoding dataset and international address depth are less consistently authoritative than the top three.

   per Claude Address data (OSM/open-data derived) is noticeably weaker than Google/HERE in rural areas and outside North America/Western Europe — not for apps needing rooftop precision globally.

   per Gemini Lacks the deep proprietary point-of-interest database and absolute edge-case accuracy of Google, particularly in developing regions.

4. 4
   HHERE Geocoding & Search—5 pts

   GPT #3Claude #4Gemini —

   Excellent international addressing, navigation-grade road context, multilingual results, and strong performance in automotive, logistics, and delivery apps; a near-tie with Mapbox when routing context matters.

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   GPT Excellent international addressing, navigation-grade road context, multilingual results, and strong performance in automotive, logistics, and delivery apps; a near-tie with Mapbox when routing context matters.

   Claude Automotive-grade address data that rivals Google in Europe and parts of Asia, a generous free tier (250k transactions/month), and clear commercial licensing — a strong pick for logistics/delivery-style mobile apps.

   Where it falls short

   per GPT More enterprise-oriented packaging and a less approachable developer experience than Mapbox or Google.

   per Claude Developer experience lags — clunkier SDKs, docs, and account setup than Google/Mapbox/Radar — and mindshare is thin, so community answers are scarce.

5. 5
   LLocationIQ—2 pts

   GPT —Claude —Gemini #4

   Delivers the best balance of simplicity, features, and cost-efficiency for budget-constrained startups, offering a highly generous free tier and simple, drop-in REST APIs.

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   Gemini Delivers the best balance of simplicity, features, and cost-efficiency for budget-constrained startups, offering a highly generous free tier and simple, drop-in REST APIs.

   Where it falls short

   per Gemini Relies heavily on OpenStreetMap data, leading to inconsistent street address formatting and missing coverage in regions with low community contributor activity.

6. 6
   BBigDataCloud—1 pts

   GPT —Claude —Gemini #5

   Achieves industry-leading sub-millisecond response times and extremely cheap pricing by optimizing specifically for administrative boundaries and neighborhoods rather than street numbers, perfect for general local content or weather apps.

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   Gemini Achieves industry-leading sub-millisecond response times and extremely cheap pricing by optimizing specifically for administrative boundaries and neighborhoods rather than street numbers, perfect for general local content or weather apps.

   Where it falls short

   per Gemini It does not support high-precision street-address or rooftop-level lookup, making it useless for delivery or navigation apps.

7. 7
   GGeoapify—1 pts

   GPT #5Claude —Gemini —

   Strong price-to-capability ratio, permissive integration options, useful confidence and result-type metadata, and OpenStreetMap-based coverage without forcing a proprietary mobile map stack.

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   GPT Strong price-to-capability ratio, permissive integration options, useful confidence and result-type metadata, and OpenStreetMap-based coverage without forcing a proprietary mobile map stack.

   Where it falls short

   per GPT OSM-derived address completeness varies materially by region, so it is not the best choice where uniformly high rooftop accuracy is mandatory.

8. 8
   OOpenCage—1 pts

   GPT —Claude #5Gemini —

   Aggregates OSM and other open datasets behind one clean API with the friendliest terms in the category — results are yours to cache and store indefinitely, pricing is flat and transparent, and formatted-address handling across countries is excellent for a small vendor.

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   Claude Aggregates OSM and other open datasets behind one clean API with the friendliest terms in the category — results are yours to cache and store indefinitely, pricing is flat and transparent, and formatted-address handling across countries is excellent for a small vendor.

   Where it falls short

   per Claude It's an HTTP API only (no mobile SDKs, no autocomplete) and inherits OSM's gaps, so precision in poorly-mapped regions trails commercial data vendors.

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Tracked by ModelsAgree · rank 1 = 5 pts … rank 5 = 1 pt · re-polled weekly