The table expands across desktop, stays dense on mobile, and highlights the strongest numeric values so the real tradeoffs are easy to spot.
Capabilities
Capabilities
| Spec | ||
|---|---|---|
| Price | N/A | N/A |
| Height | 183cm | 174cm |
| Weight | 83kg | Not officially disclosed |
| Battery Life | 4-6 hours | Not officially disclosed |
| Charging Time | Not disclosed | Not officially disclosed |
| Max Speed | 4 m/s (14.4 km/h) | 2 m/s (7.2 km/h) |
| AI | Intel i7 (real-time control) + NVIDIA Xavier (AI inference) | AgileCore platform; Google DeepMind Gemini Robotics integration (announced) |
| Sensors | High-Resolution HDR Camera (Front x2), Rear Camera, Panoramic View System | LiDAR, Cameras, Force/Torque Sensors, Tactile Sensors, Proximity Sensor, Microphones |
| Connectivity | Wi-Fi, Bluetooth | Not officially disclosed |
| Voice Assistants | None | None |
| Status | Active | Development |
| Category | Humanoid | Humanoid |
| Manufacturer | 1X Technologies | Agile Robots |
Capability matrix
Use this grid when the shortlist is already close and feature gaps become the real tiebreaker.
| Capability | EVE | Agile ONE |
|---|---|---|
| 25 Degrees of Freedom | ✓ | — |
| Autonomous Indoor Navigation | ✓ | — |
| Autonomous Navigation | — | ✓ |
| Bipedal Walking | — | ✓ |
| Dexterous Manipulation (21-joint hands) | — | ✓ |
| Dual-Arm Manipulation (heavy and fragile items) | ✓ | — |
| Dual-Wheel Self-Balancing Mobility | ✓ | — |
| Embodied AI Learning from Human Demonstrations | ✓ | — |
| Force-Controlled Grasping | — | ✓ |
| Human-Robot Interaction | — | ✓ |
| Machine Tending | — | ✓ |
| Material Handling | — | ✓ |
| Multi-Terrain Capable | ✓ | — |
| Precision Assembly | — | ✓ |
| Revo1 Quasi Direct-Drive Actuation | ✓ | — |
| Teleoperation (shared autonomy) | ✓ | — |
| Tool Use | — | ✓ |
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, Lawn & Garden, Companions 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 — 4NE-1 Mini versus 4NE-1 isolates whether the higher tier actually changes the ownership story.
Mobility platforms — CyberDog 2 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 205 robots tracked, 141 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.
