Mercury vs Mindar
Side-by-side comparison of Mercury (Apptronik, Inc.) and Mindar (Unknown) — specs, pricing, Robolist Trust Score, and verified deployments. Updated daily.
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Layer 1: Identity & Trust
Manufacturer Country
- MercuryUS
Mindar—
Year First Available
- Mercury2018
- Mindar2019
Verified Deployments
- Mercury0 Deployments
- Mindar0 Deployments
Layer 2: Operational
Price Range (USD)
- Mercury$150,000
- Mindar$909,090
Battery / Shift Runtime
- Mercury8 hrs
- Mindar48 hrs
Availability Status
- MercuryACTIVE
- MindarACTIVE
Physical Form Factor
Height
- Mercury1180 mm
- Mindar28 cm
Weight
- Mercury55 kg
- Mindar57 kg
Walking Speed
- Mercury1.2 m/s
- Mindar—
Terrain
- Mercuryindoor
- Mindarindoor
Payload & Dexterity
Payload
- Mercury1 kg
- Mindar100 kg
Total DOF
- Mercury19
- Mindar—
Arm DOF
- Mercury17
- Mindar—
Compute & AI
Onboard Compute
- MercuryJetson Orin Nano SUPER 8GB
- MindarIntel® Core™ Ultra X9 388H processor
Programming
- Mercurycode_python, code_cpp, no_code_gui
- Mindar—
Battery & Power
Runtime
- Mercury8 hrs
- Mindar48 hrs
Software
SDK Languages
- Mercurycode_python, code_cpp, no_code_gui
- Mindar—
ROS Support
- MercuryYes
- Mindar—
Open API
- MercuryYes
- Mindar—
Commercial
Price (USD)
- Mercury$150,000
- Mindar$909,090
Price Tier
- Mercury—
- Mindar¥100 million (US$909,090) total project cost
Pricing Model
- Mercury—
- Mindarpurchase
Applications
- Mercuryresearch, education, service, teleoperation
- Mindarreligious service, cultural education
| MercuryhumanoidApptronik, Inc. 51.5Trust Score | MindarhumanoidUnknown 55.8Trust Score | |
|---|---|---|
| Layer 1: Identity & Trust | ||
| Manufacturer Country (values differ) | US | — |
| Year First Available (values differ) | 2018 | 2019 |
| Verified Deployments | 0 Deployments | 0 Deployments |
| Layer 2: Operational | ||
| Price Range (USD) (values differ) | $150,000 | $909,090 |
| Battery / Shift Runtime (values differ) | 8 hrs | 48 hrs |
| Availability Status | ACTIVE | ACTIVE |
| Layer 3: Category Specific | ||
| Physical Form Factor | ||
| Height (values differ) | 1180 mm | 28 cm |
| Weight (values differ) | 55 kg | 57 kg |
| Walking Speed (values differ) | 1.2 m/s | — |
| Terrain | indoor | indoor |
| Payload & Dexterity | ||
| Payload (values differ) | 1 kg | 100 kg |
| Total DOF (values differ) | 19 | — |
| Arm DOF (values differ) | 17 | — |
| Compute & AI | ||
| Onboard Compute (values differ) | Jetson Orin Nano SUPER 8GB | Intel® Core™ Ultra X9 388H processor |
| Programming (values differ) | code_python, code_cpp, no_code_gui | — |
| Battery & Power | ||
| Runtime (values differ) | 8 hrs | 48 hrs |
| Software | ||
| SDK Languages (values differ) | code_python, code_cpp, no_code_gui | — |
| ROS Support (values differ) | Yes | — |
| Open API (values differ) | Yes | — |
| Commercial | ||
| Price (USD) (values differ) | $150,000 | $909,090 |
| Price Tier (values differ) | — | ¥100 million (US$909,090) total project cost |
| Pricing Model (values differ) | — | purchase |
| Applications (values differ) | research, education, service, teleoperation | religious service, cultural education |
Insufficient data for full comparison
The following fields had no data for any of the selected robots: Mobility Type, Humanoid Subtype, Running Capable, Stair Climbing, Payload (Peak), Hand DOF, Arm Reach, Grip Strength, Manipulation Repeatability, Bimanual Coordination, Tool Use, Compute Platform, VLM Capable, Foundation Models, Imitation Learning, Teleoperation, Battery Capacity, Charging Time, Charging Method, Battery Swap, Avg Power Consumption, Force-Limited Arms, Fall Recovery, Fall Detection Response, Emergency Stops, Human Detection Method, Safe Speed Near Humans, Simulation Platforms, Air-Gap Capable, MTBF, Task Success Rate, Deployment Maturity, IP Rating, Noise Level, RaaS / Month, Developer Unit Price, Delivery Lead Time, Warranty, Production Pilots
best in categoryweakest in categoryvalues differ
About this comparison
Mercury vs Mindar compares two robots in the humanoid category. All data is sourced from manufacturer spec sheets, verified deployments, and third-party filings; see our methodology for how the Robolist Trust Score is calculated.