Why this name?
Agent-Native
Universal Humanoid Foundation Model
Agent · VLM · WBC — a unified three-layer architecture,
the only path bridging digital intelligence and physical intelligence.
Embodied AI's core bottleneck—no general-purpose brain
Hardware is mature enough, but the industry has no universal brain — the ecosystem can't take off.
Why? Two hidden structural fractures.
Data has never really Scaled
LLMs unlocked Scaling Law with internet-scale text;
embodied data has never reached that scale —
teleop is expensive, low coverage, no scalable data engine.
Digital and physical R&D are siloed
Agents and LLMs evolve at warp speed in the digital world;
robots evolve in isolation in the physical world.
But Physical AGI = Digital AI + Physical AI.
Core Team · An Agent-Driven AI-Native Company
Full-stack coverage: LLMs, agents, motion control, robot hardware — 10 humans + N AI agents, per-capita output far above traditional teams.
Flood Sung
MetaBot · Agent-Native Org Infrastructure
An agent framework reaching from digital to physical — the gateway to Physical AGI.
MetaMemory
Skill Hub
Agent Bus
T5T · Top 5 Things
Why this is the moat
Per-capita output ≈ 50-person team
An Agent-Driven Three-Layer Unified Architecture
MetaBot · Agent Layer
ALWAYS-ONVLM · Vision-Language Brain
5–10 HzWBC · Motion Cerebellum
50–500 HzCore Technology Keywords
From the underlying method up to model-level capability, four keywords define XVI's brain.
DreamVPT
Long Context
WholeBody VLA
In-Context RL
Compositional
Generalization
Same playbook as the LLMs · Benchmark-Driven
We're building a universal humanoid foundation model — not a vertical solution. Same scaling as LLMs, same benchmark grind.
Every public humanoid benchmark — indoor, outdoor, manipulation, navigation, single-step, long-horizon — we aim to top all of them. General capability proven by hard evidence.
Indoor Manipulation
Outdoor Locomotion
Bimanual Coordination
Long-Horizon Tasks
Human-Robot Collab
Generalization
Beyond general · betting on high-value physical-world scenarios
We bet on high-value physical-world scenarios — places humans can't go, won't go, or shouldn't go.
These three directions are not capability boundaries — they're resource focus. Exclusive data, exclusive scenarios, exclusive benchmarks: a moat nobody else can replicate.
Humanoid Astronauts
Robot Hardware Engineers
Robot Lab Technicians
Claude is a general LLM · Anthropic bet on coding · topped SWE-bench · shipped Claude Code.
XVI is the universal humanoid foundation · betting on these three directions · each one a killer app of embodied AI.
General is the foundation · taste is the moat — both required, no conflict.
Model Leadership → Vertical Integration
Two-phase path — Phase 1 obsesses over the model layer to establish authority; Phase 2 launches in-house hardware toward mass-produced humanoids. Move fast first, go heavy later — never both at once.
Tech Validation
~100h real-robot seed
core PoC running
Open-Source Release
model open-sourced · arXiv paper
DeepSeek-style playbook
Mars Demo
In-Context RL closed loop
first public live demo
Model SOTA
10000h data
authority established
10 people, all-in on the model
Models + papers fully open
Top the benchmarks
Launch In-House Hardware
supply-chain build-out
in-house roadmap locked
GPT-4 Moment
full-body prototype v1
industry inflection reached
Mass Production
MARKET 01-03 first-party RaaS
data flywheel kicks in
Scale Deployment
high-value first, household last
core position in the value chain
XVI first-party humanoid RaaS
In-house humanoid · 100% data ownership
API licensing to OEMs
Funding
A clear capital allocation to fuel the full arc — from PoC to open-source release to ecosystem build-out.