Comparison controls
Swap robots without losing the table. Green cells mark numeric leaders; text rows show the tradeoffs that need judgment.
Green cells flag numeric leaders, while AI, sensors, and capability rows keep the real buying tradeoffs visible.
Capabilities
Capabilities
Capabilities
Capabilities
| Spec | ||||
|---|---|---|---|---|
| Price | $13,500 USD | $20,000 USD | $29,950 USD | ¥577,500 JPY |
| Height | 132cm (standing) | 167cm | 160cm | 43cm |
| Weight | 35kg (with battery) | 30kg | 46kg (33kg with ballast removed for transport) | 4.6kg (LOVOT 3.0; 2.0 was 4.3kg) |
| Battery Life | ~2 hours | ~4 hours | 8 hours (light CPU load) | 30-45 minutes active, then returns to nest |
| Charging Time | Not disclosed | Not disclosed | Not officially disclosed | 15-30 minutes (on charging nest) |
| Max Speed | Not disclosed | ~4 mph | Not officially disclosed | 1-2 km/h |
| AI | 8-core high-performance CPU (optional NVIDIA Jetson Orin for EDU) | 1X Embodied Intelligence | Open-source ROS 2 and Python SDK with reference autonomy demos for mapping, navigation, 3D SLAM, data collection, and VLM grasping; IEEE Spectrum reports Intel NUC 15 plus NVIDIA Jetson Orin NX onboard compute. | GPU (1,024 cores) + 32 Tensor cores + 8 CPU cores, 512GB storage (LOVOT 3.0) |
| Sensors | Depth Camera, 3D LiDAR, 4 Microphone Array, Dual Joint Encoders | RGB Cameras, Depth Sensors, Tactile Skin, Microphone Array | Wide-FOV depth sensing, High-resolution RGB cameras, Calibrated RGB + depth perception, Floor hazard sensing, Pair of hemispherical LiDARs, Luxonis vision/navigation cameras, Wrist-mounted depth camera | Horn Top Camera (half-sphere), Horn Front Camera, Depth Camera, Luminosity Sensor, Hygrometer-Thermometer, Posture Sensor, Distance Sensor, Obstacle Sensor, Touch Sensors (full body), Microphone Array (x4) |
| Connectivity | Wi-Fi 6, Bluetooth 5.2 | Wi-Fi, Bluetooth | Wi-Fi, Bluetooth, NFC, Infrared Communication | |
| Voice Assistants | None | None | None | None |
| Status | Available | Pre-order | Available | Available |
| Category | Humanoid | Humanoid | Home Assistants | Companions |
| Manufacturer | Unitree | 1X Technologies | Hello Robot | GROOVE X |
Capability matrix
Use this grid when the shortlist is already close and feature gaps become the real tiebreaker.
| Capability | G1 | NEO | Stretch 4 | LOVOT |
|---|---|---|---|---|
| 13 Degrees of Freedom | — | — | — | ✓ |
| 3D SLAM | — | — | ✓ | — |
| 55cm + 6cm Wrist Reach | — | — | ✓ | — |
| Adaptive Learning | — | ✓ | — | — |
| Assistive Teleoperation and Pilot Deployments | — | — | ✓ | — |
| Auto-Charging (returns to nest) | — | — | — | ✓ |
| Autonomous Mapping and Navigation | — | — | ✓ | — |
| Autonomous Navigation | — | — | — | ✓ |
| Bipedal Walking | ✓ | — | — | — |
| Customizable Clothing/Appearance | — | — | — | ✓ |
| Data Collection Tools | — | — | ✓ | — |
| Dexterous Hands (optional Dex3-1) | ✓ | — | — | — |
| Emotional Companionship | — | — | — | ✓ |
| Foldable Design (69cm folded) | ✓ | — | — | — |
| Gentle Manipulation | — | ✓ | — | — |
| Household Chores | — | ✓ | — | — |
| Mobile Manipulation | — | — | ✓ | — |
| OLED Eyes (organic EL displays, natural blinking) | — | — | — | ✓ |
| OTA Upgrades | ✓ | — | — | — |
| Object Manipulation | ✓ | — | — | — |
| Omnidirectional Indoor Mobility | — | — | ✓ | — |
| Open-Source Software Platform | — | — | ✓ | — |
| Person Recognition | — | — | — | ✓ |
| Personality Development Over Time | — | — | — | ✓ |
| Quick-Release Tooling | — | — | ✓ | — |
| Research Platform | ✓ | — | — | — |
| Room Mapping (360° camera) | — | — | — | ✓ |
| Safe Human Interaction | — | ✓ | — | — |
| Secondary Development (EDU) | ✓ | — | — | — |
| Self Charging | — | — | ✓ | — |
| Thermal Person Detection | — | — | — | ✓ |
| Tidying Up | — | ✓ | — | — |
| Touch Response (full body sensors) | — | — | — | ✓ |
| VLM Grasping Demos | — | — | ✓ | — |
Use this flow to get to a clean shortlist fast. The route works best as a dense research workbench, not a marketing page.
Start with robots that solve the same job. Use category anchors like Humanoid, Cleaning, Companions, Commercial before you worry about micro-spec wins.
Check price, status, battery, sensors, and capabilities before getting lost in minor spec rows.
Once you have a shortlist, hide shared rows. That turns the table from a spec dump into a real decision tool.
A dedicated cleaner versus a home assistant with cleaning features can reveal whether you really need a specialist or just broader household coverage. Compare around the same outcome, not the same marketing language.
Use a prebuilt pairing when blank-page friction is the problem. Open one, swap robots, and keep moving.
Price bracket check — Roomba Mini versus AquaSense X shows what the premium tier actually buys in navigation, maintenance, and smart-home polish.
Same-brand shortlist — M1 versus Jupiter isolates whether the higher tier actually changes the ownership story.
Mobility platforms — Go2 versus D1 Pro is a fast way to compare payload, stability, and commercial ambition inside the quadruped category.
Home presence check — Miko Mini versus LOVOT reveals how much extra presence, hardware, and ecosystem you buy as companion robots move upmarket.
Turn comparison rows into an actual recommendation — not just more reading.
Not all spec deltas matter equally. Rank your buying criteria before crowning a winner.
The sticker price is only one row. Subscriptions, consumables, and service access often decide the real winner.
Subscriptions
Cloud AI and premium app tiers can make a cheaper robot more expensive over three years.
Consumables
Brushes, pads, filters, and bags flip the value story on high-frequency robots.
Energy & battery
Large batteries and frequent charging reveal everyday operating demands.
Repair & warranty
Local servicing and spare-parts access are the quietest but most important long-term costs.
Specs describe ideal conditions. Your rooms, pets, and Wi-Fi determine what actually performs.
Of 285 robots tracked, 180 are available now. For household tasks, getting a capable robot into daily use today usually beats waiting for incremental improvements. For research or early-adopter use, waiting can make sense if the next model changes the platform story.
If two robots are still neck-and-neck, use softer signals that affect ownership quality more than spec sheets admit.
Comparison FAQ
Short answers to the questions that usually show up once the shortlist is live and the tradeoffs feel real.
