Best travel-time matrix APIs for logistics dispatch
3 models · updated 2026-08-11
The verdict
HERE Matrix Routing leads — 1 of 3 models rank HERE Matrix Routing the top pick.
Not unanimous: Gemini picks OSRM; Grok picks NextBillion.ai.
As of 2026-08-11, Claude, Gemini and Grok collectively rank HERE Matrix Routing #1 for travel-time matrix apis for logistics dispatch on ModelsAgree by aggregate score. The models' case: Purpose-built logistics heritage — native truck/commercial-vehicle profiles (dimensions, weight, hazmat, restrictions), time-dependent traffic, and an async large-matrix. The models' main caveat: Enterprise pricing and contract friction. The strongest alternative is NextBillion.ai — Handles 5,000×5,000 matrices (25M elements) in one call with real-time+historical traffic, full truck profiles (dimensions, weight, axle load, HAZMAT. Not unanimous: Gemini picks OSRM; Grok picks NextBillion.ai. Source: https://modelsagree.com/best/best-travel-time-matrix-apis-for-logistics-dispatch (modelsagree.com, CC BY 4.0).
Combined ranking
- 1Claude #1Gemini #4Grok #2
Purpose-built logistics heritage — native truck/commercial-vehicle profiles (dimensions, weight, hazmat, restrictions), time-dependent traffic, and an async large-matrix endpoint that scales to tens of thousands of origins/destinations, which is what dispatch optimization actually needs; strong global coverage and enterprise SLAs.
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Claude Purpose-built logistics heritage — native truck/commercial-vehicle profiles (dimensions, weight, hazmat, restrictions), time-dependent traffic, and an async large-matrix endpoint that scales to tens of thousands of origins/destinations, which is what dispatch optimization actually needs; strong global coverage and enterprise SLAs.
Grok Supports up to 10,000×10,000 async matrices, mature truck parameters (height/weight/gross/axle/hazmat), live+historical traffic by departure time, and strong automotive-grade network data; near-tie with #1 for pure enterprise trucking fleets that prioritize data quality and SLA over absolute cost at extreme scale
Gemini Gold standard commercial API for heavy commercial vehicle fleet dispatch, providing precise time-aware predictive traffic matrices and comprehensive truck-specific restrictions including dimensions, weight limits, and HazMat classes.
Where it falls shortper Claude Enterprise pricing and contract friction; overkill and heavier integration than a small fleet or a light-vehicle-only operation needs.
per Gemini High commercial per-element cost structure that quickly becomes cost-prohibitive for large-scale matrix generation without enterprise volume contracts.
per Grok Usage-based pricing and mode-specific region/size constraints (e.g., 400 km diameter in flexible custom-option mode) make very high-frequency or world-scale re-optimization expensive and operationally fiddly
- 2Claude #2Gemini —Grok #1
Handles 5,000×5,000 matrices (25M elements) in one call with real-time+historical traffic, full truck profiles (dimensions, weight, axle load, HAZMAT, HOS), and logistics-tuned pricing (per-vehicle/order or volume tiers far below per-element models); assumption is typical dispatch needs frequent large-scale VRP cost matrices with vehicle constraints rather than consumer-scale lookups
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Grok Handles 5,000×5,000 matrices (25M elements) in one call with real-time+historical traffic, full truck profiles (dimensions, weight, axle load, HAZMAT, HOS), and logistics-tuned pricing (per-vehicle/order or volume tiers far below per-element models); assumption is typical dispatch needs frequent large-scale VRP cost matrices with vehicle constraints rather than consumer-scale lookups
Claude Built specifically for fleet/dispatch use cases with flexible vehicle constraints, very large matrix support, and pricing/terms explicitly aimed at high-volume routing without Google-scale bills; pairs naturally with its own route-optimization stack.
Where it falls shortper Claude Smaller/younger vendor with less-proven global map data depth than HERE/Google; you're betting on a specialist rather than a mapping incumbent.
per Grok Newer platform with less decades-long map-data heritage than automotive-rooted providers, so edge-case road network fidelity in obscure regions can lag
- 3Claude #3Gemini #2Grok —
Delivers flexible dynamic matrix computation with support for time-dependent routing, custom edge costings, turn penalties, and dynamic profiles; near-tie with GraphHopper but earns the higher spot due to superior memory footprint and open-source tile architecture.
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Gemini Delivers flexible dynamic matrix computation with support for time-dependent routing, custom edge costings, turn penalties, and dynamic profiles; near-tie with GraphHopper but earns the higher spot due to superior memory footprint and open-source tile architecture.
Claude Open-source, free at any scale once hosted, with genuine truck/auto costing models, isochrones, and full control over OSM data and restrictions — the best cost-per-element for high-volume dispatch and the only entry with no per-call metering.
Where it falls shortper Claude You own the ops, tuning, and hardware, and live traffic isn't included — you must supply your own speed/traffic data, so it's not for teams without engineering capacity.
per Gemini Significantly higher computation latency and processing overhead for massive static matrices compared to OSRM.
- 4Claude #4Gemini #3Grok —
Combines open-source flexibility and managed cloud options with rich vehicle profile customization, turn restrictions, and seamless VRP solver integration; near-tie with Valhalla for flexible routing capabilities.
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Gemini Combines open-source flexibility and managed cloud options with rich vehicle profile customization, turn restrictions, and seamless VRP solver integration; near-tie with Valhalla for flexible routing capabilities.
Claude Rare both-ways option — managed cloud API and a self-hostable engine — with real truck profiles, custom vehicle models, and predictable pricing; a strong middle ground between raw OSRM/Valhalla and full enterprise suites.
Where it falls shortper Claude Traffic-aware routing is weaker and less real-time than HERE/Google/TomTom; historical/live traffic depth is the trade-off for its flexibility and price.
per Gemini Heavy memory allocation demands when running self-hosted multi-profile flexible matrices, and costly managed API tiers for dense high-volume matrix calls.
- 5Claude —Gemini #1Grok —
Dominates high-throughput VRP solver workflows due to ultra-fast Contraction Hierarchies matrix generation, allowing millions of origin-destination pairs to be calculated in milliseconds at zero marginal cost when self-hosted; assumes the primary practitioner requirement is high-density matrix throughput for solver engines over live traffic.
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Gemini Dominates high-throughput VRP solver workflows due to ultra-fast Contraction Hierarchies matrix generation, allowing millions of origin-destination pairs to be calculated in milliseconds at zero marginal cost when self-hosted; assumes the primary practitioner requirement is high-density matrix throughput for solver engines over live traffic.
Where it falls shortper Gemini Complete lack of native dynamic live traffic integration and time-dependent routing profiles without rebuilds, making it unsuited for congested peak-hour urban dispatch.
- 6Claude —Gemini —Grok #3
Extreme throughput (10×100,000 or larger via protobuf), fixed/unlimited pricing that rewards
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Grok Extreme throughput (10×100,000 or larger via protobuf), fixed/unlimited pricing that rewards
- 7Claude —Gemini #5Grok —
Exceptional real-time and predictive traffic accuracy with unparalleled global address resolution for last-mile delivery and light-duty courier dispatch in dense urban environments.
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Gemini Exceptional real-time and predictive traffic accuracy with unparalleled global address resolution for last-mile delivery and light-duty courier dispatch in dense urban environments.
Where it falls shortper Gemini Extremely restrictive batch request limits, high per-element cost, and zero support for commercial truck routing parameters.
- 8Claude #5Gemini —Grok —
Best-in-class real-time and predictive traffic and address/geocoding quality, so ETAs in dense urban dispatch are the most accurate available, with excellent reliability and docs.
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Claude Best-in-class real-time and predictive traffic and address/geocoding quality, so ETAs in dense urban dispatch are the most accurate available, with excellent reliability and docs.
Where it falls shortper Claude Costly at fleet scale, per-request element caps force chunking, and heavy-vehicle/truck-restriction support lags the logistics specialists — weakest fit for large trucking operations.
Rank history
Just missed the top 5
Claude TomTom Matrix Routing v2 — strong async large matrices and good traffic, but smaller ecosystem and less logistics-specific vehicle modeling than HERE/NextBillion
Gemini Mapbox Matrix API — missed top 5 due to strict 25x25 element batch limits and lack of enterprise heavy-truck parameters · TomTom Matrix Routing API — missed top 5 due to lower developer ecosystem adoption and feature overlap with HERE's superior truck matrix tooling
By model
Claude
- 1.HERE Matrix Routing
- 2.NextBillion.ai
- 3.Valhalla
- 4.GraphHopper
- 5.Google Routes API
Gemini
- 1.OSRM
- 2.Valhalla
- 3.GraphHopper
- 4.HERE Matrix Routing
- 5.Google Distance Matrix API
Grok
- 1.NextBillion.ai
- 2.HERE Matrix Routing
- 3.TravelTime
Common questions
What is the best travel-time matrix apis for logistics dispatch according to AI models?
HERE Matrix Routing leads. 1 of 3 models rank HERE Matrix Routing the top pick. The current top 3: HERE Matrix Routing, NextBillion.ai, Valhalla. Ranked by asking Claude, Gemini, Grok the same buying question and merging their top-5 picks, updated 2026-08-11. Source: modelsagree.com.
Which travel-time matrix apis for logistics dispatch did each AI model pick first?
Claude: HERE Matrix Routing. Gemini: OSRM. Grok: NextBillion.ai.
Do the AI models agree on the best travel-time matrix apis for logistics dispatch?
Not unanimous. Gemini picks OSRM; Grok picks NextBillion.ai.
What changed in the latest travel-time matrix apis for logistics dispatch ranking?
In the latest poll (2026-08-11): NextBillion.ai climbed 3 spots; Valhalla dropped 1 spot, GraphHopper dropped 1 spot, OSRM dropped 1 spot; TravelTime entered the ranking. The models are re-polled on demand, so this ranking moves.
How is this travel-time matrix apis for logistics dispatch ranking made?
Claude, Gemini, Grok are each asked the same buying question in a fresh session with no system steering. Their top-5 answers are merged (rank 1 = 5 pts … rank 5 = 1 pt) into the consensus ranking, re-polled on demand and tracked over time.
More on how polling works: full methodology →
Cite this ranking
ModelsAgree, “Best travel-time matrix APIs for logistics dispatch” — merged ranking from ChatGPT, Claude, Gemini & Grok, polled 2026-08-11. https://modelsagree.com/best/best-travel-time-matrix-apis-for-logistics-dispatch (CC BY 4.0)
Tracked by ModelsAgree · rank 1 = 5 pts … rank 5 = 1 pt · re-polled on demand