Figure AI vs Google DeepMind Gemini Robotics
Figure AI vs Google DeepMind Gemini Robotics: side-by-side comparison of two robotics foundation models & agent stacks systems — architecture, taxonomy, license, pricing, MCP/A2A support, and direct edges.
Figure AI · Google DeepMind Gemini Robotics
Cost & capability
| Figure AI | Google DeepMind Gemini Robotics | |
|---|---|---|
| Capability band | entry | entry |
| Capability composite | 30 | 35 |
Where they differ (11)
Rows where both sides have data and the values disagree — the shortlist of dimensions that actually distinguish these two systems.
| Figure AI | Google DeepMind Gemini Robotics | |
|---|---|---|
| Capability composite | 30 | 35 |
| Type | Humanoid robot maker (Figure 01 / Figure 02 / Helix VLA model) | Robotics foundation model from Google DeepMind |
| Created | 2022 (founded) | 2025-03 |
| Latest release | Helix VLA (Feb 2025); Figure 03 in development | Gemini Robotics 1.5 (2025) |
| Funding | $675M Series B Feb-2024 (Microsoft, OpenAI, Bezos, NVIDIA, Intel, LG Innotek; $2.6B val); reported $39.5B val funding Q2 2025 | Google DeepMind (Alphabet parent) |
| Backend storage | Internal Figure cloud | Google Cloud |
| Deployment | Direct customer deployment (humanoid robot) | Trusted-tester via partners; Vertex AI / Cloud planned |
| API surface | No public API; closed humanoid platform | Vertex AI / Google Cloud Robotics endpoint planned |
| Multi-tenancy | Per-customer fleet | Per-customer (trusted-tester) |
| Optimised for | End-to-end humanoid VLA — full-body + dexterous hand control | Robotics built on Gemini 2.0 multimodal foundation |
| Anti-fit | Closed humanoid platform — no developer API; alpha-customer-only | Closed weights; trusted-tester only; Google Cloud lock-in expected |
At a glance
| Figure AI | Google DeepMind Gemini Robotics | |
|---|---|---|
| Section | Robotics foundation models & agent stacks | Robotics foundation models & agent stacks |
| Tier | T1 | T1 |
| Type | Humanoid robot maker (Figure 01 / Figure 02 / Helix VLA model) | Robotics foundation model from Google DeepMind |
| Created | 2022 (founded) | 2025-03 |
| Latest release | Helix VLA (Feb 2025); Figure 03 in development | Gemini Robotics 1.5 (2025) |
| Funding | $675M Series B Feb-2024 (Microsoft, OpenAI, Bezos, NVIDIA, Intel, LG Innotek; $2.6B val); reported $39.5B val funding Q2 2025 | Google DeepMind (Alphabet parent) |
| Backend storage | Internal Figure cloud | Google Cloud |
| Deployment | Direct customer deployment (humanoid robot) | Trusted-tester via partners; Vertex AI / Cloud planned |
| API surface | No public API; closed humanoid platform | Vertex AI / Google Cloud Robotics endpoint planned |
| Multi-tenancy | Per-customer fleet | Per-customer (trusted-tester) |
| A2A | — | Google's own A2A protocol — likely first-party |
| Optimised for | End-to-end humanoid VLA — full-body + dexterous hand control | Robotics built on Gemini 2.0 multimodal foundation |
| Anti-fit | Closed humanoid platform — no developer API; alpha-customer-only | Closed weights; trusted-tester only; Google Cloud lock-in expected |
Taxonomy
| Axis | Figure AI | Google DeepMind Gemini Robotics |
|---|---|---|
| storage | weight | weight |
| retrieval | parametric-recall | parametric-recall |
| persistence | parametric-permanent | parametric-permanent |
| update | agent-controlled | agent-controlled |
| unit | trajectory | trajectory |
| governance | opaque | opaque |
| conflict | training-time | training-time |
Pros & cons
Figure AI
Pros: Best-funded humanoid maker; Helix VLA is one of the highest-profile robotics-FM releases of 2025; BMW pilot.
Cons: Closed platform / weights; humanoid-only; production scale still small; valuation aggressive.
Google DeepMind Gemini Robotics
Pros: Built on Gemini 2.0 (best-in-class multimodal); DeepMind RT-X lineage; Apollo + Agile Robots partners; A2A first-party.
Cons: Closed weights; trusted-tester only; Google Cloud lock-in; no developer-self-serve.