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Atlas is the better fit to watch for Hyundai factory work; Digit has the stronger public record of customer-site logistics operations. The comparison is not a head-to-head performance test: Atlas is in development and field testing, while Agility’s reported operating history is for Digit 4 and its published payload and endurance figures are preliminary estimates for Digit 5.
Atlas vs. Digit at a glance
| Comparison | Boston Dynamics Atlas | Agility Robotics Digit |
|---|---|---|
| Current status | All-electric humanoid in development, with field testing at a Hyundai facility on sequencing tasks. Boston Dynamics | Digit 4 has company-reported customer-site operations; Digit 5 is in development. Agility Robotics |
| Stated work | Hyundai’s plan begins with parts sequencing and later expands to component assembly. Hyundai Motor Group | Logistics work includes tote handling and warehouse operations; Agility also targets manufacturing, warehousing, and distribution. Agility Robotics |
| Published reach | 2.3 m (7.5 ft); the cited page does not state a comparable payload. Boston Dynamics | Digit 5: 2.2 m (7.2 ft), a preliminary vendor estimate. Agility Robotics |
| Payload and endurance | Not stated in the cited Atlas sources. | Digit 5: 23 kg (50 lb) payload, 10:1 run-to-charge ratio, and up to 20 work hours in 24 hours; preliminary estimates, not independently verified field results. Agility Robotics |
| Operational evidence | Company-described field testing and Hyundai’s future deployment plan. | Agility reports Digit 4 operating hours and a GXO tote milestone; Agility and GXO also announced a multi-year service agreement. |
What Atlas is designed to do
Boston Dynamics describes the current Atlas as an all-electric humanoid and says it is field-testing real-world sequencing tasks at a Hyundai customer facility. Its product page lists a 2.3 m (7.5 ft) reach. That published reach does not, by itself, establish payload, cycle time, or suitability for a particular production task. Boston Dynamics Atlas
Hyundai’s factory roadmap
Hyundai Motor Group has announced a phased plan: parts sequencing is expected to begin in 2028, followed by component assembly by 2030. These are planned milestones, not evidence that broad factory deployment has already happened. The announced use case is specifically factory work; a demonstration or sequencing field test should not be treated as proof of general production throughput. Hyundai Motor Group’s strategy announcement
What Digit is designed to do
Digit is aimed at moving materials in work environments such as warehouses and factories. Agility describes its broader target sectors as manufacturing, warehousing, and distribution. Its documented GXO example is logistics-oriented: Digit and Agility Arc were being deployed in warehouse operations and integrated with existing automation, including autonomous mobile robots. Agility and GXO’s announcement
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Digit 4: the operating record Agility reports
Agility’s September 2026 announcement says Digit 4 had accumulated more than 65,000 operational hours across North American customer sites, naming GXO, Schaeffler, Amazon, and Toyota Motor Manufacturing Canada. Agility also reports that Digit 4 moved a cumulative 100,000 totes at GXO’s Flowery Branch facility. These are company-reported figures, not independent audits. Agility’s September 2026 announcement Agility’s tote milestone
Digit 5: preliminary specifications
Agility’s Digit 5 page lists a 23 kg (50 lb) payload, 2.2 m (7.2 ft) reach, a 10:1 run-to-charge ratio, and up to 20 work hours in a 24-hour period. Agility identifies Digit 5 as in development and says specifications and capabilities may change; the figures are preliminary estimates based on internal testing and benchmarking of pre-production configurations. They are not guarantees of customer-site performance. Agility Robotics Digit 5
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Where the trade-offs matter
Deployment maturity
The clearest difference in the available evidence is maturity, not proven robot superiority. Atlas is being field-tested with Hyundai, with factory milestones still in the future. Digit 4 has a reported record of customer-site operations and a named GXO service agreement, while Digit 5 remains a development product. Those facts describe different generations and stages; they do not establish how either platform would perform in a new facility.
Task and facility fit
Atlas’s announced path is tied to Hyundai manufacturing, starting with parts sequencing and then component assembly. Digit’s public examples center on warehouse logistics and tote movement, with an announced GXO arrangement that describes integration into existing automation. A facility should assess the specific material flow, handoffs, workspace, and automation interfaces it needs; a broad label such as “humanoid” does not prove plug-and-play compatibility.
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What the published numbers can—and cannot—tell you
Atlas’s 2.3 m listed reach and Digit 5’s preliminary 2.2 m reach are close enough to invite comparison, but reach alone says little about task performance. The sources do not provide a comparable Atlas payload or runtime, and Digit 5’s figures are explicitly preliminary. Missing Atlas specifications are not evidence of lower capability, just as Digit’s published estimates are not independently confirmed field outcomes.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What a buyer cannot conclude from public claims
The cited sources do not establish a controlled Atlas-versus-Digit comparison for speed, uptime, safety, throughput, or total cost. They also do not provide a final comparative price or independent safety result. Agility’s operating-hour and tote figures are useful evidence of reported Digit 4 deployments, but they should not be converted into a direct score against Atlas’s field-testing statement or Hyundai’s roadmap.
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For an enterprise evaluation, request task-specific results and deployment terms for the exact platform generation under consideration. Compare the same workflow, operating conditions, integration requirements, safety controls, maintenance expectations, and recurring costs before treating either robot as a fit.
Quick Recap
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