```json { "title": "Best route optimization APIs", "url": "https://kardinal.ai/best-route-optimization-api/", "datePublished": "2026-09-18", "dateModified": "2026-09-25", "language": "en-GB", "description": "11 route optimization APIs, compared on 149 real-world constraints. Full ranking, coverage by family, and results broken down by industry.", "author": "Kardinal", "publisher": "Kardinal" } ``` # Best route optimization APIs # Best route optimization APIs > **In brief:** This benchmark compares 11 route optimization APIs across 149 constraints representative of the market. Kardinal comes out clearly ahead, followed by Solvice, its closest competitor. Functional coverage matters more than algorithmic performance: a fast engine that cannot model your critical constraints will never make it into production. Route optimization has become a decisive factor in many industries: last-mile delivery, field service, waste collection, retail distribution. In response, the market offers a long list of APIs that all seem, at first glance, to answer the same need. In practice, coverage across this ranking ranges from 14% to 93% between the first and the last vendor. This guide compares eleven solutions on their ability to model operational reality: breadth of constraints, optimization objectives, flexibility and fit with each use case. > **Looking for a sector-specific comparison?** This guide covers every solution and every constraint. For an analysis focused on your own operation: [Parcel & express](https://kardinal.ai/best-route-optimization-api-parcel-delivery/) · [Retail last mile](https://kardinal.ai/best-route-optimization-api-retail-distribution/) · [Oversized & heavy freight](https://kardinal.ai/best-route-optimization-api-oversized-heavy-freight/) · [Cold chain](https://kardinal.ai/best-route-optimization-api-cold-chain-delivery/) · [Long distance / FTL](https://kardinal.ai/best-route-optimization-api-long-haul-transport/) · [Waste collection](https://kardinal.ai/best-route-optimization-api-waste-collection/) · [Field service](https://kardinal.ai/best-route-optimization-api-field-service/) ## Key points - Full ranking across the 149 constraints: Kardinal (93%), Solvice (74%), LogisticsOS (66%), HERE (59%), Google (57%), NextBillion AI (51%), GraphHopper (40%), Timefold (32%), Verso (29%), Routific (23%), Mapbox (14%). - Only two solutions out of eleven offer lexicographic optimization (ranking objectives strictly instead of weighting them): Kardinal and HERE. - Coverage varies sharply by sector: on waste collection, Kardinal reaches 98%, against 74% for its closest competitor. - The full benchmark methodology and raw data are available, along with a pricing comparison across every vendor. > 📋 **Benchmark methodology** > > This benchmark reviews the public documentation of 11 vendors (Kardinal, Solvice, LogisticsOS, HERE, Google, NextBillion AI, GraphHopper, Timefold, Verso, Routific, Mapbox) against 149 constraints representative of the market, each retained as soon as it is available from at least two vendors. > > The constraints fall into 11 families: > > - Objectives & balancing > - Cost & fleet economics > - Route structure & limits > - Pickups, deliveries & returns > - Capacity & load compatibility > - Service time > - Assignment, continuity & access > - Shifts, breaks & working hours > - Travel time & road network > - Real time & re-optimization > - Time windows > > The [full constraint list](https://kardinal.ai/benchmark-route-optimization-api-2026/), with definitions and raw data, is available in the complete benchmark. Pricing for the eleven solutions is covered in a [dedicated comparison](https://kardinal.ai/route-optimization-api-pricing-2026-comparison/). ## Why comparing API performance makes little sense Unlike conventional benchmarks, this analysis does not focus on algorithmic performance, meaning computation speed and solution optimality. Here is why. ### The simplified-problem trap An objective performance comparison would require testing every engine on identical problems. But because the available constraints differ so much from one vendor to the next, you end up falling back on basic cases: minimizing distance with a few time windows and capacity limits. On problems that simple, every engine performs roughly the same. The gaps are marginal, simply because the problem is too easy. ### What actually matters: operational realism An algorithm that returns its best solution in seconds matters far less than an algorithm that can model your operation exactly as it runs. Take waste collection. Disposal sites often have limited intake capacity: one vehicle at a time during unloading, which takes an hour. If the optimizer cannot model that constraint and sends ten trucks in the morning, the whole day's plan collapses. The operator will never run the tool in production, however good its calculations look on paper. > ⚖️ Complete coverage means routes that can be run as planned, and therefore real operational gains. > > A fast engine with partial coverage means manual rework, wasted time, and a tool that ends up unused. That is why this benchmark puts functional coverage ahead of raw performance. ## Our selection of the 11 best route optimization APIs ### Kardinal: the most complete route optimization API on the market (93% coverage) A French company founded in 2015, Kardinal specializes in complex route optimization. The solution serves a wide range of industries: parcel delivery, e-commerce, waste collection, bulk delivery, field interventions, urban courier work. Its R&D team, which includes several PhDs in applied mathematics, built a proprietary optimization engine designed for maximum flexibility. Kardinal covers 139 of the 149 benchmark constraints, or 93%, with only 10 gaps and not a single partially covered constraint. It is the only solution in the panel to fully cover eight of the eleven constraint families: objectives, route structure, capacity, service time, shifts, travel time, real time and time windows. Its weakest family remains assignment and continuity (67%), where Solvice does just as well. Kardinal is [recognized by Gartner as a Representative Vendor](https://kardinal.ai/kardinal-recognized-representative-vendor-gartner-market-guide-for-vehicle-routing-system/) in the 2025 Market Guide for Vehicle Routing & Scheduling, the only French solution listed in that reference report. ### Solvice: the route optimization API challenging Kardinal (74% coverage) A European optimization specialist, Solvice targets complex use cases with a deeply technical approach. It posts the best score after Kardinal, carried by solid coverage across almost every family: objectives (72%), route structure (72%), capacity (89%) and above all pickups and deliveries (90%, the best score in the panel outside Kardinal). Solvice shares with Kardinal the exclusivity of several advanced cost constraints: hourly cost that depends on the time of day, cost per visit at a facility, throughput limit per site. On those specific points, they are the only two solutions on the market able to model them. Solvice also offers a customizable business dictionary and a good grasp of European regulations, but remains less well known than the long-standing leaders, with a smaller ecosystem. ### LogisticsOS: the cost-driven route optimization API (66% coverage) LogisticsOS is a US company founded in 2020 in San Francisco and a Y Combinator alumnus. Its API is built around cost optimization: usage-based billing and integration with the OpenStreetMap, TomTom and HERE Maps providers. It matches Kardinal on the cost & fleet economics family (75% each): flat rates and overtime thresholds, combined billing across own fleet and subcontractors, guaranteed minimum revenue per subcontracted resource. It also holds up well on route structure (70%) and real time (88%). For any operation where the economic trade-off between own fleet and subcontracting drives the decision, LogisticsOS is worth testing. ### HERE: the mapping-led route optimization API (59% coverage) HERE Technologies, the mapping vendor known until 2015 as Nokia HERE, offers a Tour Planning API v3: multi-vehicle optimization backed by its own real-time traffic data and dedicated truck profiles. HERE stands out with full coverage of travel time and road network (100%, tied with Kardinal and NextBillion AI). Notably, it is, alongside Kardinal, the only solution in the panel to support lexicographic optimization, the method that ranks objectives strictly rather than weighting them into a single formula. If you already run on the HERE mapping data ecosystem, its optimization API is a natural candidate to evaluate. ### Google: its route optimization API (57% coverage) Google offers a route optimization API backed by the scale of its infrastructure and its worldwide mapping data. It benefits from the excellent Google Maps base and native real-time traffic integration. The solution is decent on basic objectives and predictive traffic, but falls behind on cost (50%) and on some real-time capabilities: unlike Timefold, NextBillion AI and Solvice, Google does not fully cover live problem updates while a route is being executed. Google's infrastructure does guarantee excellent service availability, which counts when you operate at scale. ### NextBillion AI: the route optimization API built for the incremental case (51% coverage) NextBillion AI offers a mapping and optimization platform with a customizable business dictionary and native support for incremental optimization. It is strong on travel time (100%, tied with Kardinal and HERE) and real time (100%, tied with Timefold and Solvice). A fair trade-off between targeted advanced features and more modest overall coverage, to evaluate first if reacting to disruptions matters more to you than functional breadth. ### GraphHopper: the open source route optimization API (40% coverage) Open source by origin, GraphHopper also offers a commercial route optimization API. That dual nature brings transparency and an active community, with flexible deployment options: cloud or on-premise. Overall coverage stays modest, held back by gaps on the cost, capacity and assignment families. GraphHopper holds up better on travel time (92%) and shifts and breaks (71%). Today a better fit for targeted use cases than for broad coverage of business constraints. ### Timefold: the route optimization API for field service (32% coverage) Timefold is a Belgian vendor based in Ghent, founded in 2023 by a team from the OptaPlanner project, whose open source solver it took over and developed further. Its positioning targets field service and workforce management first: technician routes, team schedules, through a Java/Kotlin engine exposed as "PlanningAI" models in an API. The overall score hides high marks on specific families: 100% on real time & re-optimization, tied with Kardinal, NextBillion AI and Solvice. Timefold's strength is concentrated in a few families rather than spread across the whole scope. Relevant first for scheduling or field service cases, less so for broad route optimization coverage. ### Verso: the entry-level route optimization API (29% coverage) An entry-level API, Verso bets on simplicity and fast integration for standard needs. The API is deliberately lean, with few options, which makes it easy for technical teams to pick up. One detail does surprise: Verso reaches 100% on the service time family, tied with Kardinal, Solvice, HERE and LogisticsOS. An island of completeness in otherwise limited coverage. Suited to small fleets without sophisticated constraints, with the risk of having to switch solutions as operations grow more complex. ### Routific: the route optimization API for small fleets (23% coverage) In the same bracket as Verso, Routific offers a simple API aimed at small fleets, paired with an intuitive web app. It stands out for plug-and-play integration and a good reputation for responsive customer support. Routific clearly targets small and mid-sized businesses with standard needs: pleasant interface, quick integration, but designed for a niche market. ### Mapbox: its complementary route optimization API (14% coverage) Mapbox, a reference in mapping solutions, offers an optimization API alongside its core products. It benefits from excellent geographic data and solid predictive traffic handling, naturally integrated with the rest of the Mapbox suite. Optimization is clearly not its original business: functional coverage is the lowest in the panel. The API works more as a visualization add-on than as a genuine engine for complex optimization. ## Comparative analysis of the best route optimization APIs ### Ranking across the 149 constraints | Rank | Solution | Coverage | Positioning | |---|---|---|---| | 1 | Kardinal | 93% | Generalist, complex constraints | | 2 | Solvice | 74% | Generalist, complex use cases | | 3 | LogisticsOS | 66% | Fleet cost trade-offs | | 4 | HERE | 59% | Mapping and traffic | | 5 | Google | 57% | Global infrastructure and data | | 6 | NextBillion AI | 51% | Responsiveness and incremental | | 7 | GraphHopper | 40% | Open source, targeted cases | | 8 | Timefold | 32% | Field service, scheduling | | 9 | Verso | 29% | Entry level | | 10 | Routific | 23% | Small fleets | | 11 | Mapbox | 14% | Mapping add-on | Kardinal keeps a clear 19-point lead over its closest competitor. The rest of the ranking tightens into a dense pack between 51% and 74% (Solvice, LogisticsOS, HERE, Google, NextBillion AI), followed by a group of more specialized or entry-level solutions below 40%. What stands out most is how varied the profiles are inside that second group. HERE and LogisticsOS did not exist as generalist optimization vendors until recently, and already sit ahead of Google across these 149 constraints. Timefold, conversely, posts a modest overall score but leads on two specific families (real time, travel time), the mark of a deliberately vertical positioning. ### Coverage by constraint family | Family | Constraints | Kardinal | Solvice | LogisticsOS | HERE | Google | NextBillion AI | GraphHopper | Timefold | Verso | Routific | Mapbox | |---|---|---|---|---|---|---|---|---|---|---|---|---| | Objectives & balancing | 36 | 100% | 72% | 64% | 68% | 63% | 50% | 42% | 40% | 22% | 42% | 1% | | Cost & fleet economics | 24 | 75% | 54% | 75% | 40% | 50% | 17% | 4% | 0% | 4% | 0% | 0% | | Route structure & limits | 23 | 100% | 72% | 70% | 48% | 43% | 57% | 48% | 4% | 43% | 4% | 22% | | Pickups, deliveries & returns | 20 | 95% | 90% | 45% | 70% | 65% | 70% | 60% | 70% | 35% | 35% | 35% | | Capacity & load compatibility | 9 | 100% | 89% | 56% | 44% | 56% | 67% | 44% | 44% | 11% | 11% | 11% | | Service time | 9 | 100% | 100% | 100% | 100% | 89% | 22% | 22% | 11% | 100% | 11% | 11% | | Assignment, continuity & access | 9 | 67% | 67% | 33% | 33% | 33% | 33% | 33% | 17% | 0% | 17% | 0% | | Shifts, breaks & working hours | 7 | 100% | 71% | 71% | 43% | 71% | 57% | 71% | 36% | 36% | 43% | 36% | | Travel time & road network | 6 | 100% | 58% | 83% | 100% | 50% | 100% | 92% | 67% | 25% | 42% | 25% | | Real time & re-optimization | 4 | 100% | 100% | 88% | 63% | 50% | 100% | 0% | 100% | 63% | 25% | 0% | | Time windows | 2 | 100% | 100% | 100% | 100% | 100% | 100% | 50% | 75% | 50% | 50% | 100% | Assignment, continuity and access remain Kardinal's weakest family at 67%, and Solvice does exactly as well. Service time and time windows, on the other hand, are now market standards: most advanced vendors cover them fully or nearly so, which makes them poor criteria for telling solutions apart. ### The capabilities that genuinely set vendors apart Lexicographic optimization, which ranks objectives strictly instead of weighting them, remains the rarest constraint in the benchmark: only Kardinal and HERE support it out of the eleven solutions tested. Predictive traffic, in contrast, is now widespread: Kardinal, NextBillion AI, Solvice, GraphHopper, Google, HERE and Mapbox all cover it. Only Routific, Timefold and Verso lag behind. Real-time problem updates are no longer the preserve of a handful of long-standing vendors: Timefold, NextBillion AI and Solvice cover them fully, while Google, GraphHopper and HERE cover them only in part. ### Which API for which sector? Overall functional coverage does not tell the whole story. Two APIs with similar general coverage can have radically different strengths and gaps from one sector to the next. What you optimize weighs as much in the decision as how complex your operations are. **Waste collection** Kardinal (98%), LogisticsOS (74%), Solvice and HERE tied (73%). Limited intake capacity at disposal sites and simultaneity constraints remain the most critical points; Kardinal is still the only vendor to model them in full. [Read the full analysis](https://kardinal.ai/best-route-optimization-api-waste-collection/) **Oversized & heavy freight (charter, LTL/pallets)** Kardinal (95%), LogisticsOS (80%), Solvice (78%). This segment demands fine-grained modeling of variable costs across vehicle and load combinations, plus multi-depot optimization. LogisticsOS stands out thanks to its handling of combined own-fleet and subcontractor costs. [Read the full analysis](https://kardinal.ai/best-route-optimization-api-oversized-heavy-freight/) **Field service / technicians** Kardinal (97%), Solvice and LogisticsOS tied (78%), NextBillion AI (72%). In field service, handling skills and certifications remains the central constraint. Timefold, despite positioning itself on this sector, does not make the top three: its product targets a narrower use than route optimization at large. [Read the full analysis](https://kardinal.ai/best-route-optimization-api-field-service/) **Long distance / FTL** Kardinal (95%), Solvice (69%), LogisticsOS (66%). Full truckload transport stacks regulatory, technical and operational constraints. Solvice leads the challengers thanks to its advanced rate modeling. [Read the full analysis](https://kardinal.ai/best-route-optimization-api-long-haul-transport/) **Parcel & express** Kardinal (95%), Solvice (79%), LogisticsOS (77%). Parcel delivery remains the most demanding sector in constraint density: tight slots, high stop density, daily disruptions. [Read the full analysis](https://kardinal.ai/best-route-optimization-api-parcel-delivery/) **Retail last mile / distribution** Kardinal (97%), LogisticsOS (82%), Solvice (78%). LogisticsOS leads the challengers in this sector, carried by its modeling of combined costs across own and subcontracted routes. [Read the full analysis](https://kardinal.ai/best-route-optimization-api-retail-distribution/) **Cold chain / fresh products** Kardinal (98%), Solvice (80%), LogisticsOS (79%). Fresh product delivery combines temperature constraints, short time windows and specialized vehicle profiles. Solvice keeps its edge thanks to its rate modeling. [Read the full analysis](https://kardinal.ai/best-route-optimization-api-cold-chain-delivery/) ## How to choose and test a route optimization API The real value of an optimizer is not measured on a generic benchmark: it is measured on your data, with your constraints. Whether you run 3 vehicles or 300. Here are the criteria that actually make the difference when choosing and integrating a solution: - **Coverage of your sector's constraints.** This is the most important criterion. An API that cannot model your critical constraints will produce routes nobody can run, whatever its algorithmic performance. The sector guides break this down for each industry. - **A free tier generous enough to test on real data.** Not a handful of demo requests, but enough access to validate coverage before you commit. - **A short time to first result.** The time between your first call and a usable result says a lot about how well the API was designed. - **SDKs in your language.** Idiomatic libraries (Python, JS/TS) that behave the way your team expects, with no surprises. - **Documentation with reproducible examples.** Not just a parameter reference, but real forkable examples for each use case. - **Public, predictable pricing.** If you have to talk to a salesperson to learn the price, that is already a signal. To compare the grids, see our [2026 pricing comparison](https://kardinal.ai/route-optimization-api-pricing-2026-comparison/). At equivalent functional coverage, these criteria determine integration speed, cost predictability and your ability to iterate fast. **[→ Create a free account and start testing](https://console.kardinal.ai/)** ## Conclusion: which route optimization API should you choose? There is no single best API. What exists is a fit between your real constraints and what each solution can model. Functional coverage matters more than algorithmic performance. Kardinal covers 93% of the 149 constraints analyzed, against 74% for Solvice, the closest solution. You can check it in minutes on your own data, for free. **[→ Start with the free tier](https://console.kardinal.ai/)** · **[Read the documentation](https://developers.kardinal.ai/)** · **[See the full benchmark](https://kardinal.ai/benchmark-route-optimization-api-2026/)** ## FAQ ### Which route optimization API is the best? There is no single best API: the choice depends on your sector and your level of complexity. Kardinal is the most complete solution on the market with 93% coverage across 149 constraints, against 74% for Solvice. For simple needs, Routific and Verso are enough at an attractive price. For complex operations or sectors with critical constraints (waste collection, FTL, charter), Kardinal remains the only vendor covering almost every constraint. ### What is the difference between Kardinal and Solvice? Solvice leads the other challengers with 74% coverage, notably on pickups and deliveries (90%) and capacity (89%). Kardinal still keeps a 19-point lead overall, remains the only vendor alongside HERE to offer lexicographic optimization, and fully covers eight of the eleven constraint families analyzed, against three for Solvice (service time, real time and time windows, three families where most advanced vendors already reach 100%). ### Can you test a route optimization API for free? Yes. Kardinal offers a generous free tier, with no time limit and no sales conversation, to test the API on real data. GraphHopper also offers a self-hostable open source version, as does the Timefold solver in its Community Edition. The other solutions (Google, NextBillion AI, Routific, Solvice, LogisticsOS, HERE) offer limited trials or require a sales contact to access a full test environment. ### What is lexicographic optimization in logistics? It is a method that sets an absolute hierarchy between objectives instead of combining them into a weighted formula. It lets you express, for instance: first minimize the number of vehicles used, then, at equal vehicle count, minimize total distance. The approach avoids the tedious calibration of weighting coefficients. Of the 11 solutions tested, only Kardinal and HERE offer it. ### Which API should you choose for a fast technical integration? Kardinal is designed so that a developer gets their first routes on the very first API call, with no complex configuration. The API exposes consistent conventions, clear and actionable errors, idiomatic Python and JS/TS SDKs, and full documentation with reproducible examples. The free tier lets you run an end-to-end integration entirely on your own. --- > 💡 **Ready to test it?** Create a free account and get your first optimized routes in minutes, on your real data, with no commitment. **[Start now →](https://console.kardinal.ai/)**