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.
Price
Weight
Battery Life
Max Speed
AI
Sensors
Connectivity
Status
Category
Capabilities
| Spec | ||||
|---|---|---|---|---|
| Price | $24,950 USD | $299 USD | N/A | $20,000 USD |
| Height | 141cm | 28 cm (11 in) | 1300 mm (1.3 m) | 167cm |
| Weight | 24.5kg | 1.350 kg (Lite) / 1.475 kg (Wireless) | 34 kg | 30kg |
| Battery Life | 2–5 hours | Not officially disclosed | Not officially disclosed (46.8 V, 9000 mAh battery)Not safely comparable as a typed unit | ~4 hours |
| Charging Time | Not disclosed | Not officially disclosed | Not disclosed | Not disclosed |
| Max Speed | Not disclosed | Not officially disclosed | Not disclosed | ~4 mph |
| AI | Open-source autonomy stack (ROS 2 + Python SDK) | Open-source Python SDK with Hugging Face model/app integrations for speech, vision, and conversational behaviors | 6 TOPS NPU (int4/int8/int16/FP16/BF16/TF32), Cortex-A76×4 + Cortex-A55×4 CPU, Mali-G610 GPU; NVIDIA Isaac Sim for RL training, imitation learning via leader-follower system | 1X Embodied Intelligence |
| Sensors | Intel D405 RGBD Camera (gripper), Intel D435if RGBD Camera (head), Wide-Angle RGB Camera (head), Navigation Laser (LiDAR), Microphone Array, High Accuracy Base IMU, ArUco Fingertip Markers | 120° 12 MP autofocus wide-angle camera, 4 PDM MEMS digital microphones, 5 W speaker, Accelerometer (wireless Reachy Mini) | IMU (inferred from locomotion capability) | RGB Cameras, Depth Sensors, Tactile Skin, Microphone Array |
| Connectivity | Wi-Fi 6E, Bluetooth, Ethernet, USB | USB (Reachy Mini Lite via host computer), Wi-Fi (wireless Reachy Mini) | Wi-Fi 5, Bluetooth 5.0, Ethernet (2×), USB 2.0 (2× USB-A), USB 3.0 (1× USB-C, 1× USB-A) | Wi-Fi, Bluetooth |
| Voice Assistants | None | None | None | None |
| Status | Active | Available | Development | Pre-order |
| Category | Home Assistants | Companions | Research | Humanoid |
| Manufacturer | Hello Robot | Pollen Robotics | ROBOTIS | 1X Technologies |
Capability matrix
Use this grid when the shortlist is already close and feature gaps become the real tiebreaker.
| Capability | Stretch 3 | Reachy Mini | AI Sapiens K0 | NEO |
|---|---|---|---|---|
| 10 DOF total (2 base + lift + telescoping arm + 3-DOF wrist + gripper + 2-DOF head) | ✓ | — | — | — |
| 2kg Payload | ✓ | — | — | — |
| 6-DoF head movement | — | ✓ | — | — |
| Adaptive Learning | — | — | — | ✓ |
| Animated antennas for expressive interaction | — | ✓ | — | — |
| Assistive Care | ✓ | — | — | — |
| Audio-visual interaction (camera, microphones, speaker) | — | ✓ | — | — |
| Autonomous Navigation | ✓ | — | — | — |
| Bipedal locomotion research | — | — | ✓ | — |
| Compliant manipulation and torque control | — | — | ✓ | — |
| Customizable exterior (3D-printable covers and costume options) | — | — | ✓ | — |
| DIY kit assembly (2–3 hours) | — | ✓ | — | — |
| Dexterous Teleop Kit (accessory) | ✓ | — | — | — |
| Dynamic balancing with QDD actuators | — | — | ✓ | — |
| Embodied AI Research Platform | ✓ | — | — | — |
| Floor-to-Cabinet Reach | ✓ | — | — | — |
| Full body rotation | — | ✓ | — | — |
| Fully open-source hardware and software stack | — | — | ✓ | — |
| Gentle Manipulation | — | — | — | ✓ |
| Household Chores | — | — | — | ✓ |
| Hugging Face app ecosystem integration | — | ✓ | — | — |
| Imitation learning via leader-follower data collection | — | — | ✓ | — |
| Mobile Manipulation | ✓ | — | — | — |
| Open Source Software | ✓ | — | — | — |
| Python-programmable behaviors | — | ✓ | — | — |
| Reinforcement learning training in NVIDIA Isaac Sim | — | — | ✓ | — |
| Safe Human Interaction | — | — | — | ✓ |
| Simulation-first development workflow | — | ✓ | — | — |
| Teleoperation (Web / Gamepad / Dexterous) | ✓ | — | — | — |
| Tidying Up | — | — | — | ✓ |
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, Research 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 — N1 versus Bespoke AI Jet Bot Steam Ultra shows what the premium tier actually buys in navigation, maintenance, and smart-home polish.
Same-brand shortlist — MiPA versus 4NE-1 isolates whether the higher tier actually changes the ownership story.
Mobility platforms — Go2 versus NEURA Quadruped is a fast way to compare payload, stability, and commercial ambition inside the quadruped category.
Home presence check — StackChan 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 376 robots tracked, 228 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.
