NAO vs Pepper Robot: Education & Research Comparison

NAO and Pepper are two of the best-known humanoid robots in education and human-robot interaction research, but they are designed for fundamentally different roles.

NAO is a 58 cm bipedal humanoid built around full-body programming, locomotion, embodied AI and hands-on robotics education. Pepper is a 1.2 m-class wheeled social robot built around conversation, public-facing interaction, autonomous indoor navigation and a large chest tablet. One is closer to a compact robotics laboratory; the other is closer to a mobile social-interaction platform.

The short answer is clear: NAO is the better robot for most schools, universities and research teams choosing a platform in 2026. It is the stronger option for programming, robot motion, control, computer vision, embodied AI and multidisciplinary robotics projects—and it remains available as a supported product. Pepper is the better experimental platform only for specific social-robotics studies that benefit from adult-scale presence, a touchscreen, long battery life and wheeled navigation, particularly when an institution already owns a supported unit.

Quick verdict: Choose NAO for a new educational or research purchase, especially for coding, robotics, locomotion, perception and embodied interaction. Choose Pepper only when the research question specifically requires a larger social robot, tablet-mediated interaction or long-duration public engagement—and verify the exact hardware version, software stack, battery condition, parts access and support before acquiring one. Aldebaran’s official Pepper page states that the robot is permanently out of stock.

Anton Robots maintains detailed profiles for the NAO robot and the Pepper robot. You can also compare NAO and Pepper side by side with both models already selected in the Anton Robots comparison tool.

Last reviewed: 17 July 2026. This comparison uses NAO6 specifications and separates Pepper hardware from its version-dependent NAOqi 2.5 and Android/QiSDK software configurations. Availability, support, software access and used-market condition should be verified before procurement.

NAO vs Pepper Robot at a Glance

What Are We Actually Comparing?

This article compares NAO6 with the established Pepper platform. It does not mix NAO6 specifications with the previewed NAO7 project, and it does not assume that every Pepper has the same software environment.

That distinction is essential because both product names cover years of hardware, operating-system and software changes.

Which NAO Robot?

The NAO profile on Anton Robots describes the compact sixth-generation platform commonly known as NAO6. Current manufacturer material describes a 58 cm humanoid with 25 degrees of freedom, full-body motion, cameras, microphones, tactile sensors, sonar, inertial sensing, functional hands, Choregraphe and Python/C++ development tools.

A NAO7 project is now presented separately as a preview. This comparison does not transfer any future NAO7 capability, processor, software or availability claim to NAO6. A school or laboratory should request the exact model number, NAOqi release, included software licences, language packs and support terms in writing.

Which Pepper Robot?

Pepper is a 29.6 kg wheeled humanoid with expressive arms, a large chest tablet, cameras, microphones, touch sensors, depth and environmental sensing, and an omnidirectional base. The hardware was widely adopted for social interaction, reception, education, healthcare and research.

The software question is more complicated. Official documentation distinguishes Pepper 2.9 with Android and QiSDK from Pepper 2.5 with NAOqi, Python and Choregraphe. Two Pepper units that look almost identical may therefore require different development workflows, dependencies and maintenance plans.

More importantly, Aldebaran’s official Pepper product page now states that Pepper is permanently out of stock. Current product marketing and documentation remain online, and support resources continue to exist, but a buyer should not interpret that web presence as evidence of normal new-unit production.

The most common mistake in a NAO vs Pepper comparison is treating them as two sizes of the same robot. NAO is a bipedal robotics platform. Pepper is a wheeled social-interaction platform. Their shared heritage and overlapping APIs do not make their educational value, embodiment or procurement risk identical.

How We Compared NAO and Pepper

This comparison prioritises current manufacturer documentation, technical datasheets, developer documentation, support notices and peer-reviewed research. Marketing claims are not treated as equivalent to measured educational outcomes or research validity.

Every important statement is classified as one of four types:

• Published specification: a current technical figure from a manufacturer or official support document.
• Platform capability: a documented hardware or software function that still needs a suitable application.
• Research evidence: a study result interpreted within its sample, method and limitations.
• Procurement condition: availability, software version, battery health, support or lifecycle information that can determine whether a project is viable.

A robot creating excitement in a classroom does not prove that it improves learning by itself. A successful demonstration does not establish repeatability, and a paper using Pepper ten years ago does not prove that an institution can still buy an equivalent supported unit today. The correct comparison must connect the robot to a defined learning objective or research hypothesis.

Which Is Better: NAO or Pepper?

NAO is the better overall robot for education and research in 2026.

It wins because it combines a stronger full-body robotics curriculum, easier transport, a large installed base, current product availability and a clearer path to a supported purchase. Students can work with walking, balance, joint control, gesture, perception, speech, event handling and human-robot interaction on one compact platform.

Pepper remains valuable, but its advantages are narrower and highly use-case dependent. Its adult-scale presence, tablet, long battery life and wheeled sensing make it more suitable for social facilitation, public engagement, reception-style studies, dialogue experiments and autonomous interaction in a controlled indoor environment. Those strengths can be decisive for a laboratory that already owns Pepper.

For a new buyer, however, Pepper’s official out-of-stock status changes the recommendation. A research team should not design a multi-year programme around a discontinued hardware supply without confirming replacement parts, batteries, operating-system image, software access and local expertise.

Overall winner: NAO. Specialist HRI winner: Pepper, but only when its physical form and interface are part of the research question and the institution has a supportable unit.

Price and Availability

How much does NAO cost?

Anton Robots lists NAO from approximately $16,600. That figure should be treated as a starting point rather than a universal delivered price. Educational packages may differ by region, warranty, training, software, language configuration, spare parts, shipping and institutional support.

Before approving a purchase, request a quote that identifies:

• The exact NAO generation and model number
• The installed NAOqi version
• Choregraphe and SDK access
• Speech-recognition and text-to-speech languages
• Warranty length and repair process
• Battery age and whether a spare battery is included
• Training, curriculum content and educator onboarding
• Regional taxes, shipping and import costs

NAO6 remains presented by the current manufacturer ecosystem as a product available through a quote process. United Robotics Group also describes more than 15,000 NAO robots in use across over 70 countries, which supports the platform’s educational and research footprint without guaranteeing identical support in every region.

How much does Pepper cost?

There is no responsible current new-unit price comparison because Aldebaran says Pepper is permanently out of stock. Any Pepper price in 2026 may refer to a used robot, refurbished unit, old inventory, institutional resale, lease, maintenance package or a demonstration arrangement.

That means the headline purchase price is not enough. A low-cost used Pepper can become an expensive research asset if it has a degraded battery, unavailable credentials, an unsupported software image, damaged base sensors, missing charging equipment or no practical repair route.

The Pepper profile on Anton Robots is useful for understanding the platform and discussing sourcing, but every offer should be verified at serial-number and software-version level.

Price and availability winner

NAO wins. It is possible to define a new supported procurement path. Pepper may still be obtainable, but the transaction needs the diligence normally applied to legacy laboratory equipment.

Design, Size and Classroom Fit

NAO stands approximately 58 cm tall and weighs 5.48 kg. One trained adult can carry it between a laboratory, classroom and event space, although safe handling procedures are still necessary. Its small scale also makes it practical for tabletop preparation, floor-based demonstrations and student teams working close to the robot.

Pepper is approximately human-torso height and weighs 29.6 kg. Its physical presence is one of its strongest research variables: participants can address it more like a standing social partner, presenter or staff member. The tablet remains visible during conversation, and the mobile base allows the robot to reposition on smooth indoor floors.

The trade-off is operational. Pepper needs more storage space, accessible routes, charging access and careful movement between rooms. It cannot handle normal stairs, has limited obstacle and slope capability, and its official protection class is IPX0. It belongs indoors, away from water and environmental exposure.

Classroom-fit verdict: NAO is easier to share across classes, store and supervise. Pepper creates a stronger public-facing presence but demands a more suitable facility and operating plan.

Which Is Better for Learning Programming?

NAO is the better general programming platform for robotics education.

It provides a direct connection between code and visible whole-body behaviour. A student can change a joint trajectory, walking sequence, perception event, spoken response or interaction state and immediately see the consequence in the robot’s movement. That physical feedback is powerful in project-based learning because software, mechanics, sensing, control and human factors are not isolated from one another.

Choregraphe provides a low-code entry point for sequencing behaviours, while the SDK enables deeper programming. This supports a progression from prepared activities to event-driven logic, custom behaviour, perception pipelines and external AI services.

However, institutions should examine the age of the official software stack before building a modern computer-science curriculum around it. The NAO6 documentation centres on NAOqi 2.8, and current support downloads include a legacy Python SDK. That does not make NAO unusable, but it may require virtual environments, containers, bridges, external services or a carefully maintained teaching image.

Pepper can also teach programming. Pepper 2.9 uses Android and QiSDK, which may fit teams experienced in Android development, Java or Kotlin-style workflows. Pepper 2.5 uses the older NAOqi/Python/Choregraphe environment. The problem is not a lack of programmability; it is that the correct course design depends on the exact Pepper configuration.

Programming winner: NAO for most robotics curricula. Pepper 2.9 may be attractive for a specialised Android-based social-robotics module, but buyers cannot assume that every Pepper supports that workflow.

Which Is Better for Robotics Education?

NAO is closer to a complete small-scale robotics system. Its 25 degrees of freedom include articulated legs, arms, head, pelvis and hands. Students can investigate:

• Forward and inverse kinematics
• Joint-space and Cartesian motion
• Bipedal gait and balance
• Sensor fusion and inertial feedback
• Foot contact and force sensing
• Gesture generation and expressive motion
• Vision, audio and event-driven interaction
• Behaviour design and autonomous state machines
• Human-robot interaction and social signalling

Pepper teaches a different kind of robotics. Its wheeled base removes the complexity of bipedal balance but enables work on indoor navigation, obstacle awareness, service-robot behaviour and multimodal communication. Students can combine movement, speech, tablet interfaces and user flow into a single application.

For mechanical, mechatronics, control or general robotics programmes, NAO offers the broader embodiment. For service design, interaction design and social computing, Pepper may align more directly with the course objective.

Robotics-education winner: NAO.

Which Is Better for Human-Robot Interaction Research?

There is no universal HRI winner because the robot’s body is part of the experiment.

NAO’s small, child-like appearance can reduce perceived physical threat and may suit studies involving play, peer-like roles, learning companions, rehabilitation support or interactions where the robot should appear less authoritative. Its ability to walk and use full-body gestures adds embodied cues that a screen-based agent cannot reproduce.

Pepper’s larger body, tablet and stable mobile base make it better suited to facilitator, tutor, receptionist or public-information roles. A 2026 study using both platforms explicitly assigned Pepper the role of tutor and interaction leader while framing NAO as a novice peer, using differences in size, appearance and perceived authority as part of the experimental design.

A direct 2024 comparison in which NAO and Pepper facilitated the same empathy-mapping task found significant differences in perceived human-likeness but no significant difference in the overall HRI experience in its 38-participant sample. That result is useful precisely because it warns researchers not to assume that the larger robot automatically produces a better interaction.

HRI verdict: choose the morphology that tests the hypothesis. NAO is stronger for peer-like, playful and fully embodied interaction. Pepper is stronger for adult-scale facilitation, tablet-supported dialogue and public-facing roles.

Mobility, Balance and Embodiment

NAO walks on two legs. Its body therefore exposes students and researchers to balance, gait generation, foot contact, fall risk and the coordination of many joints. The robot can sit, stand, turn, gesture, dance and combine locomotion with speech and perception.

This is a major educational advantage, but it creates practical costs. Bipedal movement is slower and less stable than a wheeled base. Falls can interrupt sessions, damage hardware or introduce experimental variability. A robust protocol should define floor surface, safety distance, recovery procedure and which motions are permitted with students nearby.

Pepper uses an omnidirectional three-wheel base with an approximate maximum speed of 2 km/h. It can move smoothly on suitable indoor surfaces without solving the balance problem of legged locomotion. Its base includes lasers, infrared sensors, sonar and bumpers that support navigation and obstacle awareness.

Pepper’s mobility is more operationally useful for reception and public-space research, but it is not a general mobile robot for rough terrain. The technical specification lists a low obstacle threshold and a maximum stationary slope of 5 degrees. It should not be expected to negotiate stairs, uneven outdoor ground or normal environmental exposure.

Mobility verdict: NAO wins for locomotion, control and whole-body embodiment research. Pepper wins for stable indoor navigation and long social-interaction sessions.

Hands, Gestures and Physical Manipulation

Neither robot should be purchased for useful payload handling.

NAO has articulated arms and functional hands that support pointing, waving, grasp demonstrations and expressive interaction. Its small scale makes the gestures readable without creating industrial-force expectations. The hands are valuable for teaching coordination and symbolic manipulation, not for moving meaningful loads.

Pepper also has expressive arms, wrists and hands, but its design prioritises communication. It can gesture toward the tablet, point, wave and accompany speech with upper-body motion. It is not designed as a material-handling or laboratory-manipulation robot.

For experiments involving object grasping, force control or dexterous manipulation, both platforms may be the wrong category. A robotic arm, cobot or research manipulator will provide more useful payload, repeatability and tooling.

Manipulation verdict: NAO offers more full-body robotics value; neither is a serious manipulation platform.

Perception and Sensors

NAO6 includes two front-facing 5 MP head cameras, four omnidirectional microphones, speakers, head and hand touch sensing, foot bumpers, sonar, an inertial unit and force-sensitive resistors in each foot. This sensor mix supports visual tracking, audio interaction, contact detection, balance and basic environmental awareness.

Pepper has a broader sensor package for social navigation. Official technical documentation lists two 5 MP cameras, stereo/depth imaging, four microphones, head and hand touch areas, wheel bumpers, six base lasers, infrared sensors, front and rear sonar and an inertial measurement unit. The chest tablet also has its own camera and sensors.

More sensors do not automatically produce better research. Sensor access, calibration, timestamping, field of view, software version, processing latency and reproducibility matter more than the count. Pepper’s richer base perception is useful for navigation and participant approach studies. NAO’s foot sensing and bipedal body are more valuable for balance and embodied-control work.

Sensor verdict: Pepper wins for breadth and mobile-environment sensing. NAO’s sensors are better aligned with legged robotics and compact embodied experiments.

Speech, Conversation and Generative AI

Both robots can speak, listen and execute dialogue flows, but neither should be described as having human-level conversational understanding by default.

NAO and Pepper were developed around structured dialogue, speech services, behaviours and application logic. Their onboard Intel Atom-era computing platforms are not equivalent to a modern GPU workstation or current AI accelerator. Advanced speech recognition, vision-language models, large language models and retrieval systems will usually rely on external local or cloud compute.

NAO now has manufacturer-presented activity tools that incorporate generative AI for non-technical users. Researchers can also build external architectures in which the robot handles sensing, motion and expression while another computer provides language, vision or planning. The same architectural principle can be applied to Pepper through QiSDK, NAOqi, chatbot integrations or custom middleware.

The critical research question is latency and control. A conversational demo can fail because of network delay, microphone conditions, speech-recognition errors, turn-taking logic or unsafe model output—not because the robot lacks a face. Experiments should log prompts, model version, response timing, confidence, failures and fallback behaviour.

AI verdict: no inherent winner. NAO is the safer current platform to build around; Pepper’s tablet and social presence can create a richer interface when a supportable unit is already available.

Battery Life and Daily Lab Operation

Battery life is Pepper’s clearest hardware advantage.

The current NAO6 datasheet states approximately 60 minutes of active use or 90 minutes of normal use, with about 90 minutes to charge. Actual runtime varies with walking, audio, CPU load, Wi-Fi use, battery age and temperature. A full teaching day requires charging breaks, spare batteries or a schedule built around shorter sessions.

Pepper’s technical support documentation states a minimum of 7 hours, typical runtime of 12 hours and maximum of 20 hours under its defined conditions. This supports full-day exhibitions, longitudinal interaction sessions and repeated participant studies. The trade-off is a full charge time of approximately 8 hours 20 minutes while switched off.

Battery condition is especially important in the used Pepper market. A robot that originally ran through a full day may no longer do so after years of storage and cycling. Ask for measured runtime under a representative workload, not only the battery percentage displayed at startup.

Battery winner: Pepper.

Software, SDKs and Version Risk

NAO and Pepper share historical software heritage, but their current development paths should not be simplified into “both use NAOqi”.

NAO software

Current NAO6 documentation points developers to NAOqi 2.8, Choregraphe and the SDK. Choregraphe helps non-experts build behaviours visually, while C++ and Python allow deeper control. The platform also has a long history of examples, academic code and community knowledge.

The limitation is software age. Teams should test operating-system compatibility, Python version, certificate requirements, network security, dependency installation and CI workflows before promising a frictionless modern development experience.

Pepper software

Official documentation separates Pepper 2.9 with Android/QiSDK from Pepper 2.5 with Python/NAOqi and Choregraphe. QiSDK provides APIs for conversation, motion, perception and autonomous abilities, while older projects may depend on legacy Python packages and NAOqi services.

This version split can become a reproducibility problem. A paper may say “Pepper” without documenting whether the robot ran 2.5 or 2.9, which libraries were used, or how dialogue and navigation were implemented. A laboratory purchasing Pepper for replication must obtain the exact software history.

Software verdict: NAO wins on procurement clarity and educational continuity. Pepper 2.9 may provide the more familiar modern app-development pattern, but Pepper’s lifecycle and configuration risk outweigh that advantage for most new buyers.

ROS, Simulation and External Compute

Neither robot should be purchased on the assumption that it is a current open ROS 2 reference platform with a modern onboard GPU.

Both have community packages, research integrations and simulation options. Researchers have used external computers, ROS bridges, virtual environments and simulators to extend NAO and Pepper beyond their native software. These approaches are valuable, but the maintenance burden belongs to the laboratory.

Before committing, run a proof of concept that confirms:

• The exact APIs required by the project
• Supported operating systems and language versions
• Network connectivity and firewall requirements
• Camera and audio-stream access
• Timing, latency and synchronisation
• Simulator fidelity for the intended experiment
• Whether required community packages are actively maintained
• How the system recovers when external compute disconnects

Developer-access verdict: both can support serious research, but neither eliminates integration engineering. NAO is the lower-risk starting point for a new programme because the underlying robot remains commercially supported and easier to replace.

Safety, Privacy and Research Ethics

NAO is smaller and lighter, but it can still fall, pinch fingers, collide or move unexpectedly. Pepper is heavier, mobile and capable of entering a participant’s personal space. Neither robot should be operated around children, patients or members of the public without a written procedure.

A deployment or study should define:

• Who supervises the robot and can stop it
• Permitted motions, speeds and operating zones
• Fall and collision procedures
• Charging, battery and cable safety
• Participant consent and age-appropriate assent
• Whether audio, video, transcripts or biometric inferences are stored
• Where cloud services process data
• Retention, access control and deletion policy
• How the study avoids misleading users about the robot’s intelligence or emotional understanding
• Accessibility and inclusion for participants who cannot use speech, vision or touch interfaces in the expected way

Claims that a robot “understands emotion” require particular care. A system may classify facial, vocal or behavioural cues and select a programmed response, but that is not evidence of human-like empathy. Researchers should describe the actual model, signal, accuracy, context and failure modes.

Safety verdict: NAO is easier to manage physically. Pepper may be more stable during normal movement, but its mass, base motion and legacy condition require stronger operational controls.

Reliability, Maintenance and Lifecycle

NAO’s current status gives it the advantage. A supported new purchase can include a warranty, training and a defined repair process. The platform is mature, but bipedal joints, hands, cameras, microphones and batteries still require care.

Pepper’s mechanical base, tablet, battery, sensors and articulated upper body make it a substantial asset to maintain. Because new supply has ended, the laboratory must assess whether replacement components and qualified service will remain accessible for the planned project duration.

For either robot, record:

• Serial number and hardware revision
• Operating-system and firmware versions
• Battery installation date and measured runtime
• Repair and part-replacement history
• Software licences, accounts and recovery credentials
• Calibration status
• Known sensor or joint faults
• Local service contact and expected response time

Lifecycle winner: NAO.

What Does Research Say About NAO and Pepper?

The academic record supports both robots as useful research platforms, but it does not support a universal claim that one robot improves learning or interaction in every context.

A 2024 direct comparison used NAO and Pepper to facilitate the same empathy-mapping activity with 38 participants. Participants perceived differences in human-likeness, but the study reported no significant difference in the overall HRI experience. This suggests that morphology changes perception without automatically changing every interaction outcome.

A 2026 multi-robot educational study deliberately used Pepper as the tutor and interaction leader and NAO as a novice peer. The role assignment leveraged their visible differences in scale and perceived authority. This is a strong example of choosing the robot body as part of the pedagogy rather than asking which specification sheet is “better”.

Another 2026 classroom study examined a Pepper-based coding activity with 29 third-grade pupils. It reported a statistically significant pre-to-post improvement in coding scores, while the authors were careful not to claim that Pepper alone caused the outcome. The teacher, activity design, workload and engagement were all part of the learning environment.

The practical conclusion is conservative: the robot is an educational medium, not the curriculum. Learning objectives, teacher orchestration, activity design, participant characteristics and assessment quality determine whether the deployment is valuable.

Best Robot by Education and Research Use Case

Explore more educational robots, humanoid robots and the Aldebaran brand profile before selecting a platform. The correct robot may also be a mobile base, robot arm, companion robot or simulation environment rather than NAO or Pepper.

NAO Robot Pros and Cons

Pros

• Available through a current quote and support ecosystem
• Compact 58 cm form and manageable 5.48 kg weight
• 25 degrees of freedom across a fully articulated bipedal body
• Useful for programming, control, locomotion, perception, AI and HRI
• Two 5 MP cameras, four microphones and multimodal sensors
• Choregraphe for low-code behaviour creation
• Python and C++ development options
• Large historical installed base and academic literature
• Strong project-based-learning fit
• Expressive movement without Pepper’s transport and storage demands
• Suitable for peer-like and child-friendly interaction roles
• Current manufacturer tools include generative-AI-assisted activities

Cons

• Approximately 60 to 90 minutes of datasheet runtime is short for a teaching day
• Bipedal falls can interrupt sessions and damage hardware
• Official software components include legacy language and dependency constraints
• Onboard compute is limited for modern vision-language or large-model workloads
• Small hands are not useful for meaningful payload manipulation
• Speech recognition and dialogue performance depend on environment, language and services
• Price is high relative to simulation-only teaching tools
• Curriculum quality still depends on educator preparation
• NAO6 buyers should consider the transition toward the previewed NAO7 project

Pepper Robot Pros and Cons

Pros

• Strong human-scale social presence
• Integrated 1280 × 800 multitouch chest display
• Typical 12-hour battery specification for long sessions
• Omnidirectional wheeled mobility on suitable indoor floors
• Rich sensor package for navigation and participant awareness
• Expressive arms, head, LEDs, speech and gestures
• Well-known platform in social robotics and HRI literature
• Suitable for facilitator, reception and public-engagement roles
• Pepper 2.9 supports Android and QiSDK development
• Large historical installed base with extensive examples and documentation

Cons

• Official Aldebaran page states that Pepper is permanently out of stock
• Used or refurbished condition can vary significantly
• Software differs between NAOqi 2.5 and Android/QiSDK 2.9 units
• 29.6 kg platform is harder to transport, store and share
• Approximately 8 hours 20 minutes for a full powered-off charge
• IPX0 and indoor-only operating assumptions
• Limited obstacles and slopes; no stairs
• No meaningful payload or manipulation capability
• Onboard compute is dated for modern AI workloads
• Long-term parts, battery and service access need verification
• Replicating older research may be difficult without the same hardware and software configuration

Total Cost of Ownership

The purchase price is only one part of the educational or research budget.

A NAO total-cost model should include:

• Robot, software and educational package
• Shipping, tax and import costs
• Spare battery and charger strategy
• Warranty and repair shipping
• Teacher or researcher training
• Protective operating area and storage case
• Computers, network and external AI services
• Time required to maintain legacy dependencies
• Curriculum development and experiment preparation

A Pepper total-cost model should add:

• Technical inspection before purchase
• Battery replacement risk
• Freight and safe building access
• Verification of charger, accessories and credentials
• Software-image recovery and version migration
• Specialist repair access and spare-part sourcing
• Contingency for irreparable failure or inability to replace the unit
• Research redesign if a second equivalent Pepper cannot be sourced

The more important metric is educational or research output: courses supported per year, students served, experiments completed, successful sessions, staff hours required, reproducibility achieved and the value of publications or learning outcomes produced.

NAO can be evaluated as a current educational asset. Pepper should be evaluated as legacy research infrastructure.

Questions to Ask Before Buying NAO or Pepper

1. What exact learning objective or research hypothesis requires a physical humanoid?
2. Does the project require walking, wheeled navigation, a tablet or only social embodiment?
3. Which exact hardware generation and software version will be supplied?
4. Can the required SDK run on the institution’s managed computers?
5. Which speech languages and cloud services are included?
6. How will audio, video and participant data be protected?
7. What measured battery runtime does the specific unit achieve?
8. Who repairs the robot, and what is the expected turnaround?
9. Are replacement batteries, joints, tablet parts and chargers available?
10. Can the project be reproduced if the robot fails or another unit is needed?
11. Does a simulator or lower-cost robot meet the same objective?
12. What teacher, technician or research-engineer time is budgeted?

Use the Anton Robots finder when the task is clear but the right robot category is not. A visually impressive humanoid is not automatically the best teaching or research instrument.

Who Should Choose NAO?

NAO belongs at the top of the shortlist when most of the following are true:

• You are making a new purchase rather than maintaining an existing Pepper lab
• The curriculum covers robotics, mechatronics, control or embodied AI
• Students need to program visible full-body behaviour
• Walking and balance are educationally relevant
• The robot must move between classrooms or events
• You need a platform that can be replaced or expanded through a current supplier route
• Peer-like, playful or child-friendly embodiment fits the interaction
• Sessions can be organised around shorter battery windows
• Your technical team can manage the NAOqi toolchain and external AI integrations

Review the full NAO price, specifications and availability profile and request confirmation of the exact software and educational package before ordering.

Who Should Choose Pepper?

Pepper remains worth using when most of the following are true:

• Your institution already owns a functional, supported Pepper
• The robot’s adult-scale social presence is central to the study
• The experiment requires an integrated touchscreen
• Long battery life is more important than bipedal embodiment
• You are studying reception, facilitation, dialogue or public interaction
• The environment has smooth floors, accessible routes and secure indoor storage
• The team knows whether the unit uses Pepper 2.5 or 2.9
• You have spare parts, battery support and a failure contingency

A new buyer should treat the Pepper listing as a sourcing and due-diligence starting point, not as proof of normal new-production inventory.

Common NAO vs Pepper Comparison Mistakes

• Calling Pepper a larger NAO: Pepper is wheeled, tablet-centred and designed around social service interaction.
• Ignoring Pepper’s out-of-stock status: lifecycle risk is now a core comparison criterion.
• Assuming all Pepper robots run the same software: Pepper 2.5 and Pepper 2.9 require different development planning.
• Mixing NAO6 with NAO7 preview claims: compare the product that can actually be quoted.
• Counting sensors without checking access: an inaccessible or poorly synchronised sensor may not help the experiment.
• Calling manufacturer emotion features human-like empathy: describe the actual perception and response pipeline.
• Assuming engagement equals learning: novelty can increase attention without proving durable educational outcomes.
• Using a single demonstration as a reliability test: repeat the task over realistic sessions and participant groups.
• Ignoring battery age: especially dangerous when sourcing Pepper used.
• Choosing morphology after designing the study: robot size, movement and authority can alter participant behaviour.
• Assuming onboard compute is enough for modern AI: most advanced applications need external processing.
• Buying hardware without budgeting staff time: integration, session preparation and maintenance often dominate cost.

FAQs

Is NAO better than Pepper?

Yes for most new education and research purchases in 2026. NAO is currently available, portable and better suited to programming, locomotion, robotics and embodied AI. Pepper is better only for specific social-interaction studies that require its larger presence, tablet, wheeled navigation or long battery life.

Which robot is better for education, NAO or Pepper?

NAO is the better overall educational robot. It supports a wider robotics curriculum and is easier to move between classes. Pepper can be more effective for social communication, service design and tablet-mediated activities when a working unit is already available.

Which robot is better for research?

It depends on the research question. Choose NAO for locomotion, control, cognition, perception, embodied AI and peer-like HRI. Choose Pepper for adult-scale social interaction, public engagement, dialogue, tablet interfaces and indoor navigation studies.

Can you still buy Pepper robot?

Aldebaran’s official Pepper page states that Pepper is permanently out of stock. Used, refurbished or legacy inventory may still be offered, but buyers should verify the serial number, hardware revision, software version, battery, accessories, repair route and ownership credentials.

Can you still buy NAO robot?

NAO6 remains presented through the current manufacturer ecosystem with a quote process. Availability, delivery time, region, software package and support should still be confirmed before purchase.

How much does NAO cost?

Anton Robots lists NAO from approximately $16,600. The final price can vary by location, support, training, software, warranty, accessories, tax and shipping.

How much does Pepper cost?

There is no reliable current new-unit price because the official product page says Pepper is permanently out of stock. Any 2026 offer may be used, refurbished, old stock or part of a service package.

How tall are NAO and Pepper?

NAO6 is approximately 58 cm tall. Pepper is approximately 1.2 m class, creating a much larger adult-facing social presence.

How much do NAO and Pepper weigh?

NAO6 weighs 5.48 kg. Pepper weighs 29.6 kg without packaging or optional plates.

Does NAO walk?

Yes. NAO is a bipedal robot with articulated legs and feet. Walking, balance and fall management are important parts of its educational and research value.

Does Pepper walk?

No. Pepper moves on an omnidirectional three-wheel base. It can navigate suitable indoor floors but cannot reproduce bipedal locomotion.

Which robot has more degrees of freedom?

NAO has 25 degrees of freedom. Pepper has 20. The numbers describe different bodies, so they should not be treated as a complete measure of capability.

Which robot has better battery life?

Pepper. Its technical documentation states a typical runtime of 12 hours, with a range from 7 to 20 hours under stated conditions. The NAO6 datasheet states about 60 minutes of active use or 90 minutes of normal use.

Which robot charges faster?

NAO. Its current datasheet lists approximately 90 minutes, while Pepper’s powered-off full charge is approximately 8 hours 20 minutes.

Which robot is easier to program?

NAO is easier to specify for a new educational programme because NAO6 has a clearer Choregraphe and NAOqi 2.8 path. Pepper programming depends on whether the unit uses NAOqi 2.5 or Android/QiSDK 2.9.

Do NAO and Pepper use Python?

NAO supports Python through its official SDK, although institutions should verify the exact legacy Python version and operating-system compatibility. Pepper 2.5 uses Python/NAOqi workflows, while Pepper 2.9 is centred on Android and QiSDK.

Can NAO or Pepper use ChatGPT or another LLM?

Yes through an integration, but the large model normally runs on an external server, cloud service or modern local computer. The robot handles audio, movement and interaction while middleware manages prompts, safety, latency and responses.

Do NAO and Pepper support ROS?

Community and research integrations exist, but neither should be assumed to be a current plug-and-play ROS 2 platform. Test the exact package, operating system, API access and maintenance status before buying.

Which robot has better sensors?

Pepper has the broader navigation and interaction sensor package, including stereo/depth imaging, lasers, infrared and front/rear sonar. NAO has the more relevant sensor configuration for bipedal balance, including foot force sensors and an inertial unit.

Which robot is safer around children?

NAO is smaller and lighter, which reduces some physical risks, but it can still fall or pinch. Pepper is stable on wheels but much heavier. Both need supervision, a defined operating area and age-appropriate safety procedures.

Can NAO or Pepper work outdoors?

Neither is an outdoor robot. Pepper’s technical specification lists IPX0, and both platforms should be used in controlled indoor conditions unless the supplier provides written approval for a specific environment.

Can NAO or Pepper carry objects?

Only very light demonstration objects within carefully controlled activities. Neither robot is designed for useful material handling. Choose a robot arm, cobot or manipulator for payload work.

Which is better for autism or special education?

NAO is more commonly aligned with compact, predictable and peer-like interaction, and the manufacturer presents it for inclusive education. However, effectiveness depends on the learner, educator, protocol and evidence base. Neither robot should replace qualified educational or clinical professionals.

Which is better for language learning?

Both can support structured speaking, repetition and role-play. NAO is easier to deploy across classrooms; Pepper’s screen and larger presence can support multimodal activities. Speech recognition, accent, noise and novelty effects should be tested with the actual learner group.

Which robot is better for a university HRI lab?

NAO is the safer new purchase because it is available and covers more robotics domains. Pepper remains highly valuable when the lab already owns one and the research focuses on social facilitation, authority, public interaction or tablet-mediated communication.

Should a school buy NAO or use simulation?

Use simulation when the goal is scalable coding, algorithms or introductory robotics at low cost. Buy NAO when physical embodiment, sensing, real-world uncertainty, human interaction and visible full-body motion are essential learning objectives.

Should I buy NAO or a used Pepper?

Choose NAO unless Pepper’s specific morphology, tablet and long-duration social role are essential to the project. A used Pepper requires deeper technical and lifecycle due diligence than a current NAO purchase.

Final Verdict

NAO wins the NAO vs Pepper comparison for most education and research buyers in 2026.

NAO is smaller, lighter, currently obtainable and more broadly useful for teaching robotics. Its 25-degree-of-freedom bipedal body lets students and researchers connect code to walking, balance, gesture, perception, speech and social behaviour. It is not a modern high-performance AI computer, its battery life is limited and parts of the official developer stack are legacy—but those constraints can be planned around within a supported current platform.

Pepper remains one of the most recognisable social robots ever deployed. Its 29.6 kg human-scale body, chest tablet, expressive upper body, rich navigation sensors and typical 12-hour battery life make it unusually strong for public interaction, social facilitation and long-duration HRI. The decisive limitation is lifecycle: Aldebaran says Pepper is permanently out of stock, and the development environment varies between NAOqi 2.5 and Android/QiSDK 2.9.

The correct decision is therefore not “small Pepper or large NAO”. It is:

• NAO for a current, portable and multidisciplinary robotics education or research platform.
• Pepper for a specialised social-interaction experiment when the institution already has a verified, maintainable unit.

Review the complete NAO robot profile and Pepper robot profile, or compare NAO and Pepper side by side with both robots preselected. For a new purchase, define the educational outcome or research hypothesis first, then validate software, support, battery, privacy and total cost before selecting the body that participants will interact with.

Primary Sources

• United Robotics Group NAO product overview and education/research applications
• United Robotics Group NAO6 developer documentation
• Maxtronics NAO6 current product page, tools and quote route
• NAO6 technical datasheet, version 10/2024
• United Robotics Group Pepper product overview
• Official Pepper 2.9 QiSDK and Pepper 2.5 NAOqi developer documentation
• Aldebaran Pepper specifications and official permanent out-of-stock notice
• Pepper technical specifications, updated January 2025
• Official Pepper QiSDK documentation
• Buchem, Tutul and Bäcker: direct NAO and Pepper empathy-mapping comparison
• 2026 multi-robot education study using Pepper as tutor and NAO as novice peer
• 2026 Pepper-based primary-school coding activity study