Three humanoid robots, three very different strategies, three price points spanning two orders of magnitude. Here’s how they stack up.
Quick Comparison
| Feature | Unitree G1 | Figure 02 | Tesla Optimus Gen 3 |
|---|---|---|---|
| Price | ~$16,000 | Not disclosed (~$100K+) | Not disclosed (~$50K+) |
| Height | 127 cm | 170 cm | 173 cm |
| Weight | 35 kg | 60 kg | 57 kg |
| DOF | 23-43 (configurable) | 40+ | 22+ |
| Battery | ~2 hours | ~5 hours | ~8 hours (estimated) |
| Target Market | Research & education | Warehouse logistics | Factory automation |
| Availability | Shipping now | Limited deployment | Internal use + limited |
| Open SDK | Yes | No | No |
Unitree G1: The Research Workhorse
What It Is
The G1 is Unitree’s entry-level humanoid — deliberately affordable, deliberately open. At $16,000, it’s the cheapest full humanoid robot you can buy, and it comes with a complete SDK for custom development.
Strengths
Price-to-capability ratio: Nothing else comes close. For the cost of a decent used car, you get a bipedal humanoid with dexterous hands, depth cameras, and a full ROS 2 stack.
Open development: Full API access, ROS 2 integration, and an active community. University labs worldwide use it as their standard research platform.
Iteration speed: Small, light, and relatively cheap to repair. When it falls over (and it will), the cost of replacement parts is manageable.
Weaknesses
Not production-ready: The G1 is a research tool, not a factory worker. Reliability and runtime aren’t sufficient for commercial deployment.
Limited payload: At 35 kg and 127 cm, it can’t handle the same tasks as full-sized humanoids.
Consumer-grade components: The actuators and sensors are good for the price but don’t match industrial-grade alternatives.
Best For
University research labs, robotics education programs, AI companies developing humanoid algorithms without needing a production robot.
Figure 02: The Logistics Specialist
What It Is
Figure AI’s second-generation humanoid, designed specifically for warehouse and logistics operations. Currently deployed at BMW’s Spartanburg manufacturing plant.
Strengths
Real-world deployment: Unlike many competitors, Figure 02 is actually working in a real factory, handling real logistics tasks. This operational data is invaluable.
Full-size form factor: At 170 cm, it operates in human-scale environments without modification.
BMW partnership: Having a major automotive manufacturer as a launch customer provides credibility and a clear path to scale.
Weaknesses
Narrow focus: Optimized for logistics means it may struggle with tasks requiring fine manipulation or diverse environments.
Closed ecosystem: No public SDK or API. You work with Figure AI’s team or not at all.
Limited availability: Production volumes are still in the low hundreds. Getting one requires a partnership agreement.
Best For
Large enterprises with warehouse or logistics operations looking for a turnkey humanoid solution with vendor support.
Tesla Optimus Gen 3: The Scale Play
What It Is
Tesla’s humanoid robot, now in its third generation. Primarily deployed in Tesla’s own factories, with external sales expected in H2 2026.
Strengths
Manufacturing DNA: Tesla knows how to build things at scale. When Optimus goes to mass production, the cost curve will drop faster than any competitor.
Battery technology: Leveraging Tesla’s automotive battery expertise gives Optimus the longest runtime of any humanoid.
Vertical integration: Tesla builds its own motors, batteries, AI chips (Dojo), and training infrastructure. No dependency on external suppliers.
FSD synergy: Tesla’s Full Self-Driving neural network expertise directly transfers to robot perception and navigation.
Weaknesses
Internal priority: Tesla primarily uses Optimus for its own factories. External availability and support are secondary concerns.
Closed system: No SDK, no API, no third-party development. You get what Tesla gives you.
Overpromise history: Tesla has a track record of ambitious robotics timelines that slip. Evaluate based on what’s shipping, not what’s promised.
Best For
High-volume manufacturing environments, especially if you’re already in the Tesla ecosystem. Long-term, this may be the most economically viable option due to scale economics.
The Real Question: Which Matters Most?
These three robots represent three different bets:
- Unitree bets on openness — Make it cheap and accessible, let the ecosystem figure out the applications
- Figure bets on specialization — Nail one use case (logistics) before expanding
- Tesla bets on scale — Use internal demand to drive down costs, then expand externally
History suggests that the winner in robotics won’t be the one with the best technology — it’ll be the one that solves the unit economics first. That race is just getting started.
Buying Guide
| If You Are… | Choose | Why |
|---|---|---|
| Research lab | Unitree G1 | Open SDK, affordable, active community |
| Logistics company | Figure 02 | Purpose-built, real deployment track record |
| Large manufacturer | Wait for Optimus | Scale economics will eventually win |
| Startup building on humanoids | Unitree G1 + custom | Fastest iteration cycle |
| Investor evaluating the space | Watch all three | Different strategies, unclear winner |