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Robot brains

AI stacks compared: what actually drives each robot

The AI brain that drives a robot is a different thing from its body, and the stacks diverge sharply. DEPLOY tracks 59 verified brain records. Some are captive: Helix is a proprietary dual-system vision-language-action model that runs only Figure's own robots, and 1X's Redwood and Tesla's FSD-derived stack follow the same vertically integrated pattern. Others are open and licensable: NVIDIA GR00T and Physical Intelligence's pi0 are foundation models other makers can build on. Many driver stacks (Waymo, Zoox, Nuro, WeRide) keep their architecture undisclosed, which DEPLOY records as an honest gap rather than guessing.

Brain records are sourced from the DEPLOY registry. How we verify.

59
Verified brain records
45
Powering at least one robot
8
Open source
45
Foundation models and VLAs

Captive, third-party, or research-only

Beyond what kind of model a brain is, the sharpest axis is who can use it. DEPLOY's framework names four provider architectures:

  • Captive (vertically integrated): Brain entity exists under the same corporate state as the hardware it powers. Not licensable to third parties; vertically integrated. The brain entity's roadmap, capabilities, and commercial trajectory are inseparable from the hardware roadmap.
  • Third-party foundation model: Brain entity licensed or deployed across multiple unaffiliated hardware partners. Foundation-model-tier capability scope (cross-domain manipulation, cross-platform deployment). The brain entity's roadmap is partner-agnostic; commercial trajectory tied to broad adoption rather than a single hardware customer.
  • Hybrid (captive + third-party): Brain entity has both captive-deployment AND third-party-licensing channels. The brain powers a parent's hardware AND is licensable to unaffiliated partners. Distinct from pure-captive (no licensing) and pure-third-party (no captive hardware).
  • Research-only: Brain entity in development or laboratory stage; no verified commercial deployment. May target captive or third-party future architecture but the framework records the current state as research, not commercial.

Undisclosed is not unknown-away

When a maker does not publish how its brain is built, DEPLOY records the architecture as not disclosed rather than inventing one. That gap is itself a finding: the most secretive stacks are often the most commercially advanced driver systems, where the architecture is the competitive moat.


Foundation models and VLAs

Vision-language-action and end-to-end driving models: the generalist stacks that translate perception into motor action.

BrainArchitectureAccessDeveloperPowers these robotsDEPLOY maturity
Not disclosedProprietaryAurora InnovationAurora Driver on Peterbilt 579 (PACCAR), Aurora Driver on International LT (2nd-gen), Volvo VNL Autonomous, Aurora DriverCommercial
Tesla FSD-BotCaptive (vertically integrated)
Neural-net brain derived from the Tesla FSD stack plus Dojo training. V3 runs on the Tesla AI5 chip (roughly 5x memory bandwidth of predecessor). On-device, vision-based, shares architecture with Tesla vehicles.ProprietaryTeslaTesla Optimus, Tesla Robotaxi (Model Y ADS), Cybercab, SemiPilot
Not disclosedProprietaryNuroNuro R2, Nuro R3, Nuro Autonomous PriusPilot
Not disclosedProprietarySkydioSkydio X10, Skydio X10D, Skydio DockProduction
Not disclosedProprietaryAvrideAvride Robotaxi (Hyundai Ioniq 5), Avride delivery robotPilot
Not disclosedProprietaryEmbark TrucksEmbark Autonomous Truck, Embark DriverResearch
Not disclosedProprietaryGatikGatik Autonomous Box Truck, Gatik Autonomous DriveCommercial
Not disclosedProprietaryAgiBotAgiBot Yuanzheng A2, AgiBot Lingxi X2Pilot
Dual-system VLA. System 2: VLM (NVIDIA-Eagle + SmolLM-1.7B) at roughly 10 Hz. System 1: diffusion transformer producing real-time motor actions. Jointly trained end-to-end on real-robot trajectories, human videos, and synthetic data. Runs on Jetson AGX Thor at the edge.Open sourceNVIDIAAEON, DigitResearch
Dual-system VLA. System 2 (S2): onboard internet-pretrained VLM, 7B params, 7-9 Hz. System 1 (S1): fast reactive visuomotor policy, 80M params, 200 Hz. Helix-02 added System 0, a 1 kHz neural prior trained on 1,000+ hours of human motion data, replacing roughly 109,504 lines of hand-engineered C++. Runs on embedded low-power onboard GPUs, no cloud.ProprietaryFigure AIFigure 02, Figure 03Commercial
Not disclosedProprietaryKodiak AIKodiak RoboTruck, Kodiak DriverCommercial
Not disclosedProprietaryPlusPlus SuperDrive Autonomous Truck, PlusDrivePilot
Not disclosedProprietaryShield AIShield AI V-BAT, Anduril Fury (YFQ-44A)Production
Not disclosedProprietaryUBTech RoboticsWalker S2, Walker S LitePilot
Vision-centric VLA (Tesla-FSD-style, vision-only), shared across Xpeng EVs, robotaxis, and the IRON humanoid. Trained on a 30,000+ GPU cloud cluster. Runs on the Xpeng Turing AI chip.Open sourceXPeng RoboticsXPeng IRON, XPENG RobotaxiPilot
Not disclosedProprietaryWaabiVolvo VNL Autonomous, Waabi Driver Autonomous TruckPilot
Not disclosedProprietaryWaymoWaymo Driver (6th gen), Waymo Via (autonomous trucking)Commercial
Not disclosedProprietaryZiplineZipline Platform 1 (Zip), Zipline Platform 2 (P2)Production
Not disclosedProprietaryBaiduApollo RT6Commercial
Hybrid stack: Boston Dynamics Atlas control software (including Orbit skill-sharing) integrated with Google DeepMind Gemini Robotics foundation models for higher-level reasoning and learning.ProprietaryBoston Dynamics, Google DeepMindAtlasPilot
Not disclosedProprietaryBot AutoBot Auto Autonomous TruckCommercial
Cognitive hybrid translating natural language into precise physical actions. Emphasis on human-like hand dexterity for fine-manipulation tasks.ProprietarySanctuary AIPhoenixCommercial
Not disclosedProprietaryEinrideEinride PodCommercial
VLA built on Gemini 2.0 with physical actions as output modality, plus an intermediate reasoning layer for spatial analysis and safety. Gemini Robotics-ER is the embodied-reasoning VLM companion. Gemini Robotics On-Device runs locally, network-independent, and is fine-tunable with 50-100 demonstrations. Gemini Robotics 1.5 emphasizes a 'think before acting' chain-of-thought style.ProprietaryGoogle DeepMindApolloResearch
Not disclosedProprietaryGalbotGalbot G1Research
Large language model (System 2 reasoning) deployed as the conversational and high-level instruction layer of Tesla Optimus's dual-brain stack. Paired with Tesla's FSD-derived visuomotor neural networks (System 1, see /brains/tesla-fsd-bot).ProprietaryxAITesla OptimusPilot
Not disclosedProprietaryIntBotJosé (IntBot humanoid)Pilot
Not disclosedProprietaryMentee RoboticsMenteeBotResearch
Redwood AICaptive (vertically integrated)
160M-parameter vision-language-action (VLA) transformer; onboard, ~5Hz; end-to-end mobile manipulationProprietary1X TechnologiesNEOPilot
Not disclosedProprietaryRobot EraRobotEra L7Pilot
Not disclosedProprietaryStack AVStack AV Autonomous Truck (Peterbilt 579)Research
Not disclosedProprietaryTorc RoboticsAutonomous Freightliner Cascadia (Torc)Pilot
Not disclosedProprietaryTuSimpleTuSimple Autonomous TruckResearch
Not disclosedProprietaryWeRideRobotaxi GXRCommercial
Not disclosedProprietaryZooxZoox RobotaxiPilot
Dexterous robot foundation model (VLA) for sustained autonomous operation on a pair of stationary dual robotic arms (the Dyna Robotics 'Dynasaur' system, not humanoid).ProprietaryDyna RoboticsNo registry robot yetCommercial
Physics-first, embodiment-agnostic field/mobility autonomy foundation models for GPS-/map-denied unstructured environments (navigation + mobile autonomy without maps/GPS/pre-defined trajectories).ProprietaryField AINo registry robot yetCommercial
Embodied/manipulation foundation model (generalist VLA-class) trained on raw physical-interaction data; ~7B-param scaling phase transition reported.ProprietaryGeneralist AINo registry robot yetResearch
VLA flow model, roughly 3B-parameter VLM backbone, motor commands at up to 50 Hz, cross-embodiment across 8 platforms: UR5e, Bimanual UR5e, Franka, Bimanual Trossen, Bimanual ARX, Mobile Trossen, Mobile Fibocom. Trained on internet-scale vision-language data, Open X-Embodiment, and Physical Intelligence's dexterous-manipulation dataset. PyTorch and JAX implementations.Open sourcePhysical IntelligenceNo registry robot yetResearch
Vision-language-action model built on pi0; co-trained on heterogeneous multi-robot + web data with high-level semantic subtask prediction for open-world generalization.Open sourcePhysical IntelligenceNo registry robot yetResearch
Multimodal any-to-any autoregressive sequence model (~8B params); next-token prediction over text/images/video/robot-actions/sensors.ProprietaryCovariantNo registry robot yetResearch
Robot foundation model; specific architectural details are limited in public disclosure this pass and should be firmed at next pass.ProprietaryRoboForceNo registry robot yetPilot
8B parameter VLM initialized from vision-language model for grounding (pointing, counting, object localization). Navigation via pointing (infers image coordinates of target location) with fallback to metric displacements. Trained with prefix-caching (tree-based attention masking, 22x token reduction) and online RL (CISPO algorithm, +3.2% improvement).ProprietaryMistral AINo registry robot yetResearch
Unified 'omni-bodied' foundation model controlling any robot form without prior body-form knowledge (quadrupeds, humanoids, tabletop arms, mobile manipulators). Trained on online human videos plus physics simulations across thousands of form factors. Built-in force-limiting safety constraints.ProprietarySkild AINo registry robot yetCommercial
End-to-end embodied driving foundation model (AV2.0); paired with GAIA latent-diffusion generative world models (sim/training) + LINGO VLA interpretability layer.ProprietaryWayveNo registry robot yetPilot

World models

Models that predict how the physical world evolves, used for planning, simulation, and policy learning.

BrainArchitectureAccessDeveloperPowers these robotsDEPLOY maturity
Unitree's open-source unified-large-model series for general-purpose robot learning across multiple embodiments. UnifoLM-WMA-0 (world-model–action): a world model of robot–environment physical interaction, used both as a simulation engine for synthetic data and as a policy-enhancement head that predicts future environmental states (video prediction translated into limb actions). UnifoLM-VLA-0 (vision–language–action): a VLA for general-purpose humanoid manipulation, built on a UnifoLM-VLM base. Open-sourced on Unitree's GitHub (WMA-0 Sept 2025; VLA-0 Jan 2026).Open sourceUnitree RoboticsUnitree G1, Unitree R1, Unitree H1, Unitree H2Research
Generative world model enabling learning by predicting outcomes versus exhaustive pre-programming; combined with VLA control for action generation.Proprietary1X TechnologiesNEO, EVECommercial
Not disclosedProprietaryPony AIPony Gen-7 RobotaxiCommercial
Self-supervised joint-embedding predictive video world model (~1.2B params); action-conditioned V-JEPA 2-AC variant for robot control.Open sourceMetaNo registry robot yetResearch

Frameworks

Open robot-learning frameworks that host and train other brains rather than drive a robot directly.

BrainArchitectureAccessDeveloperPowers these robotsDEPLOY maturity
Not disclosedProprietaryAeroVironmentAeroVironment Puma, AeroVironment P550Production
Open-source robot-learning framework. Library-style hosting of VLA models (pi0, pi0.5, GR00T N1.5) plus datasets, simulation environments (LIBERO, Meta-World), training tooling, multi-GPU support, plugin system. Released v0.4.0 with the upgrades above.Open sourceHugging FaceNo registry robot yetProduction

OS-layers and autonomy stacks

Autonomy operating systems licensed to hardware makers as the driving layer of their machines.

BrainArchitectureAccessDeveloperPowers these robotsDEPLOY maturity
Not disclosedProprietaryAnduril IndustriesAnduril Roadrunner, Anduril Bolt, Anduril Fury (YFQ-44A), Ghost (Ghost-X), Dive-LD, Ghost Shark (XL-AUV)Production
Cloud-connected autonomy OS: teach-and-repeat / mapped autonomous routing with onboard sensor-based obstacle avoidance, plus a cloud portal and mobile app for fleet management and reporting. Licensed to OEMs as the autonomy layer of their cleaning hardware.ProprietaryBrain CorpSoftBank Whiz, Tennant X4 ROVR, ICE Cobi 18, Nilfisk Liberty SC60, Tennant T7AMRProduction
Not disclosedProprietaryMobileyeVolvo EX90, Mobileye Drive, VW ID. Buzz ADPilot
Hybrid neural and symbolic multimodal cognitive stack. Plus Neuraverse, a shared OS and learning platform that connects robots so that one robot's learned skill propagates to others. NEURA's CES 2026 robots are powered by NVIDIA Isaac GR00T XX; Neuraverse is the orchestration layer atop GR00T.ProprietaryNEURA Robotics4NE-1, MiPAPilot
Not disclosedProprietaryWingWing Delivery AircraftProduction

Research models

Research-stage brains not yet carried into a commercial product in the registry.

BrainArchitectureAccessDeveloperPowers these robotsDEPLOY maturity
Not disclosedProprietaryXiaomiXiaomi CyberOneResearch
7B-parameter VLA. Architecture and training-data details pending firmer primary-source confirmation (OpenVLA paper at openvla.github.io and arXiv).Open sourceGoogle DeepMindNo registry robot yetResearch
Transformer VLA trained on web text and images, directly outputs robot actions. Instantiations on PaLM-E and PaLI-X. RT-2-X is 55B parameters. Chain-of-thought reasoning for long-horizon planning. Trained on web data plus Open X-Embodiment.ProprietaryGoogle DeepMindNo registry robot yetResearch

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Browse the registryAll verified answers

Brain records are drawn from the DEPLOY registry: reviewed Brain entities with their developer companies and the models they power. Architecture is the record's own disclosed detail, or marked not disclosed where the maker has not published it. Maturity is DEPLOY's verified stage. The captive vs third-party provider-architecture label renders only where DEPLOY has editorially classified the brain, and states honest absence otherwise. How we verify

Related answers

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All robot brainsAutonomy: verified vs claimedAll humanoid robots

Brain developers in the registry

Part ofRobot brains/Humanoid robots/Robotaxis

See also: all robot brains, autonomy verified vs claimed, humanoid robots.

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