Best robotics foundation model
4 models · updated 2026-07-15
The verdict
Gemini Robotics 1.5 leads — 0 of 4 models rank Gemini Robotics 1.5 the top pick.
Not unanimous: ChatGPT picks NVIDIA Isaac GR00T N1.7; Claude picks π0.5; Gemini picks OpenVLA; Grok picks NVIDIA Isaac GR00T N-Series.
Your vendor missing? Check any brand →
Combined ranking
- 1GPT #2Claude #2Gemini —Grok —
Strongest demonstrated general-purpose VLA for semantic, visual, action, and task generalization, with cross-embodiment transfer and unusually capable long-horizon reasoning when paired with Gemini Robotics-ER
+ model takes & fixes− hide details
GPT Strongest demonstrated general-purpose VLA for semantic, visual, action, and task generalization, with cross-embodiment transfer and unusually capable long-horizon reasoning when paired with Gemini Robotics-ER
Claude The highest raw capability in the category — embodied reasoning (ER 1.5 via the Gemini API), agentic multi-step planning, cross-embodiment transfer, and an on-device variant; near-tie with GR00T N1.5, ranked above it on capability, below π0.5 on access.
Where it falls shortper GPT Limited partner access and no open weights make it unsuitable for practitioners needing self-service deployment or deep customization
per Claude The full VLA is gated behind a trusted-tester program rather than open weights, so most teams can only touch the ER reasoning layer via API — not for anyone who needs to own and modify the policy.
- 2GPT —Claude —Gemini #1Grok #5
Provides the strongest open-source zero-shot performance and semantic language grounding for manipulation tasks (near-tied with π0, which we rank second due to deployment compute costs), serving as the standard baseline for custom fine-tuning.
+ model takes & fixes− hide details
Gemini Provides the strongest open-source zero-shot performance and semantic language grounding for manipulation tasks (near-tied with π0, which we rank second due to deployment compute costs), serving as the standard baseline for custom fine-tuning.
Grok Best open-source baseline—outperforms larger closed models like RT-2-X on diverse embodiments with efficient fine-tuning/LoRA/quantization; accessible, community-supported for typical practitioners experimenting/customizing on varied hardware.
Where it falls shortper Gemini Its autoregressive token generation limits control frequency to 5-10 Hz, making it unsuitable for highly dynamic, high-speed physical reactions.
per Grok Smaller scale than frontier closed models; requires more task-specific data/fine-tuning for peak real-world dexterity in complex dynamic settings.
- 3GPT —Claude —Gemini —Grok #1
Leading open, commercially viable VLA foundation model for humanoids with massive scaling via EgoScale (20k+ hours egocentric video), Cosmos integration for rapid synthetic data, proven validation on real bimanual/loco-manipulation across Unitree G1, Agility, etc.; broad ecosystem/adopters and simulation-to-real strengths make it highest real-world value for practitioners building/deploying general-purpose systems.
+ model takes & fixes− hide details
Grok Leading open, commercially viable VLA foundation model for humanoids with massive scaling via EgoScale (20k+ hours egocentric video), Cosmos integration for rapid synthetic data, proven validation on real bimanual/loco-manipulation across Unitree G1, Agility, etc.; broad ecosystem/adopters and simulation-to-real strengths make it highest real-world value for practitioners building/deploying general-purpose systems.
Where it falls shortper Grok Still emerging in full production-scale deployments; best for teams with simulation/GPU resources, not pure low-compute edge without fine-tuning.
- 4GPT #1Claude —Gemini —Grok —
Best overall practitioner value: an open, commercially usable 3B VLA backed by a complete workflow for teleoperation, synthetic data, simulation, post-training, evaluation, ROS, and Jetson deployment; near-tied with Gemini on model quality but substantially easier to obtain and adapt
+ model takes & fixes− hide details
GPT Best overall practitioner value: an open, commercially usable 3B VLA backed by a complete workflow for teleoperation, synthetic data, simulation, post-training, evaluation, ROS, and Jetson deployment; near-tied with Gemini on model quality but substantially easier to obtain and adapt
Where it falls shortper GPT Optimized primarily for humanoids and still requires embodiment-specific data, serious NVIDIA compute, and extensive validation
- 5GPT —Claude #1Gemini —Grok —
The strongest openly available generalist VLA — π0/π0.5 weights and the openpi codebase are public, it demonstrated genuine open-world generalization (cleaning unseen homes, long-horizon manipulation), and it has become the de-facto base model practitioners actually fine-tune on their own robots via LeRobot/openpi; rank assumes the practitioner wants a model they can run and adapt, not just admire.
+ model takes & fixes− hide details
Claude The strongest openly available generalist VLA — π0/π0.5 weights and the openpi codebase are public, it demonstrated genuine open-world generalization (cleaning unseen homes, long-horizon manipulation), and it has become the de-facto base model practitioners actually fine-tune on their own robots via LeRobot/openpi; rank assumes the practitioner wants a model they can run and adapt, not just admire.
Where it falls shortper Claude Needs serious GPU compute and quality teleop data to fine-tune well, and Physical Intelligence offers no commercial support or hardware ecosystem — you assemble the stack yourself.
- 6GPT —Claude —Gemini —Grok #2
Strongest dexterity and open-world generalization (compositional skills, unseen environments like kitchens/laundry via flow-matching + RECAP); real deployments with partners, steerable emergent capabilities position it as top for versatile physical performance across arms/manipulators.
+ model takes & fixes− hide details
Grok Strongest dexterity and open-world generalization (compositional skills, unseen environments like kitchens/laundry via flow-matching + RECAP); real deployments with partners, steerable emergent capabilities position it as top for versatile physical performance across arms/manipulators.
Where it falls shortper Grok Partnership/access focused (not fully self-hostable for all); more research-oriented for cutting-edge generalization than turnkey production for broad hardware.
- 7GPT —Claude —Gemini #2Grok —
Leverages flow matching to generate continuous motor commands at 50 Hz, enabling extremely smooth control (near-tied with OpenVLA for manipulation capability, but requires heavier compute) and complex dual-arm manipulation.
+ model takes & fixes− hide details
Gemini Leverages flow matching to generate continuous motor commands at 50 Hz, enabling extremely smooth control (near-tied with OpenVLA for manipulation capability, but requires heavier compute) and complex dual-arm manipulation.
Where it falls shortper Gemini The continuous diffusion sampling process is computationally heavy, requiring high-end local GPU acceleration for real-time edge inference.
- 8GPT —Claude —Gemini —Grok #3
Optimized end-to-end for humanoid upper-body dexterity (high-rate continuous control, onboard low-power inference, single weights for diverse household/logistics tasks); tight hardware-software integration delivers proven real-robot manipulation without heavy fine-tuning.
+ model takes & fixes− hide details
Grok Optimized end-to-end for humanoid upper-body dexterity (high-rate continuous control, onboard low-power inference, single weights for diverse household/logistics tasks); tight hardware-software integration delivers proven real-robot manipulation without heavy fine-tuning.
Where it falls shortper Grok Primarily tied to Figure robots/ecosystem; less open or transferable for arbitrary general-purpose hardware compared to broader VLAs.
- 9GPT —Claude —Gemini #3Grok —
Unmatched end-to-end integration with the Isaac Lab simulation pipeline and Jetson Thor compute, accelerating sim-to-real transfer for humanoid whole-body control.
+ model takes & fixes− hide details
Gemini Unmatched end-to-end integration with the Isaac Lab simulation pipeline and Jetson Thor compute, accelerating sim-to-real transfer for humanoid whole-body control.
Where it falls shortper Gemini Highly vendor-locked to NVIDIA proprietary hardware and software ecosystem, limiting flexibility and portability.
- 10GPT —Claude #3Gemini —Grok —
Open weights plus the most complete practitioner ecosystem — Isaac Sim/Lab integration, synthetic-data pipelines (GR00T-Dreams), cross-embodiment humanoid support, and commercial backing that de-risks adoption for teams standardizing on NVIDIA hardware.
+ model takes & fixes− hide details
Claude Open weights plus the most complete practitioner ecosystem — Isaac Sim/Lab integration, synthetic-data pipelines (GR00T-Dreams), cross-embodiment humanoid support, and commercial backing that de-risks adoption for teams standardizing on NVIDIA hardware.
Where it falls shortper Claude Humanoid-centric and ecosystem-locked — its value drops sharply if you're not on NVIDIA's sim/hardware stack, and out-of-the-box dexterity trails π0.5 and Gemini on unstructured manipulation.
- 11GPT #3Claude —Gemini —Grok —
The strongest broadly accessible cross-embodiment manipulation model, with open checkpoints, JAX and PyTorch implementations, 10,000-plus hours of pretraining, strong open-world generalization, and excellent fine-tuned LIBERO results
+ model takes & fixes− hide details
GPT The strongest broadly accessible cross-embodiment manipulation model, with open checkpoints, JAX and PyTorch implementations, 10,000-plus hours of pretraining, strong open-world generalization, and excellent fine-tuned LIBERO results
Where it falls shortper GPT Adaptation remains compute- and data-intensive, and performance can be unreliable on embodiments unlike Physical Intelligence’s training platforms
- 12GPT #5Claude —Gemini #5Grok —
A credible commercial omni-bodied foundation model spanning humanoids, quadrupeds, mobile manipulators, and industrial arms, with real deployment partnerships and a useful hierarchy combining high-level behavior with fast low-level control
+ model takes & fixes− hide details
GPT A credible commercial omni-bodied foundation model spanning humanoids, quadrupeds, mobile manipulators, and industrial arms, with real deployment partnerships and a useful hierarchy combining high-level behavior with fast low-level control
Gemini Universal commercial model designed to run across diverse morphologies (wheels, arms, quadrupeds) with robust physical recovery capabilities.
Where it falls shortper GPT Closed, engagement-based access and sparse reproducible evaluation make capability and cost difficult for independent practitioners to verify
per Gemini Closed-source and restricted to proprietary API integration, which limits developer autonomy and offline customization.
- 13GPT #4Claude —Gemini —Grok —
The most convincing whole-body humanoid system demonstrated in real environments, integrating vision, touch, language, locomotion, balance, dexterous manipulation, and multi-minute task execution; near-tied with the leaders on embodied capability
+ model takes & fixes− hide details
GPT The most convincing whole-body humanoid system demonstrated in real environments, integrating vision, touch, language, locomotion, balance, dexterous manipulation, and multi-minute task execution; near-tied with the leaders on embodied capability
Where it falls shortper GPT Proprietary and effectively inseparable from Figure 03 hardware, so it is not a practical foundation model for outside robot developers
- 14GPT —Claude —Gemini —Grok #4
Excellent long-horizon reasoning, spatial/multi-view understanding, and agentic capabilities via Gemini backbone; strong partnerships (Boston Dynamics Atlas, Apptronik) for industrial/general deployment.
+ model takes & fixes− hide details
Grok Excellent long-horizon reasoning, spatial/multi-view understanding, and agentic capabilities via Gemini backbone; strong partnerships (Boston Dynamics Atlas, Apptronik) for industrial/general deployment.
Where it falls shortper Grok Limited public access (partner-only); higher latency/compute demands vs. compact on-device options.
- 15GPT —Claude —Gemini #4Grok —
Extremely lightweight and modular transformer-based diffusion policy that runs on commodity edge GPUs and easily adapts to custom robot configurations.
+ model takes & fixes− hide details
Gemini Extremely lightweight and modular transformer-based diffusion policy that runs on commodity edge GPUs and easily adapts to custom robot configurations.
Where it falls shortper Gemini Lacks the rich visual-semantic grounding of larger models, struggling to process complex, multi-step natural language instructions.
- 16GPT —Claude #4Gemini —Grok —
The fully open, Apache-licensed 7B workhorse — transparent training recipe, huge academic adoption, strong fine-tuned results with the OFT recipe, and the easiest model to inspect, ablate, and publish against.
+ model takes & fixes− hide details
Claude The fully open, Apache-licensed 7B workhorse — transparent training recipe, huge academic adoption, strong fine-tuned results with the OFT recipe, and the easiest model to inspect, ablate, and publish against.
Where it falls shortper Claude An aging architecture trained largely on Open X-Embodiment data — zero-shot and long-horizon performance clearly trail the 2025-generation models, so it's a research baseline more than a production brain.
- 17GPT —Claude #5Gemini —Grok —
Purpose-built for the typical practitioner's actual budget — sub-1B parameters, trains and runs on a single consumer GPU, tight LeRobot integration with cheap arms (SO-100/101), making it the lowest-friction on-ramp to real VLA work.
+ model takes & fixes− hide details
Claude Purpose-built for the typical practitioner's actual budget — sub-1B parameters, trains and runs on a single consumer GPU, tight LeRobot integration with cheap arms (SO-100/101), making it the lowest-friction on-ramp to real VLA work.
Where it falls shortper Claude Small-model ceiling — it cannot match frontier generalization or dexterity, so it suits learning, prototyping, and narrow tasks rather than a genuinely general-purpose robot.
Just missed the top 5
GPT SmolVLA — exceptional low-cost open option for consumer hardware, but materially weaker on long-horizon and whole-body generality · Physical Intelligence π0.6 — promising experience-driven improvement, but not released as a generally usable practitioner model
Claude Figure Helix — impressive in-house humanoid VLA but fully proprietary — no weights, API, or access for anyone outside Figure
Gemini RT-2 — retains strong semantic reasoning but requires massive cloud-based compute infrastructure, making local real-time control impractical · RFM-1 — commercial roadmap and accessibility became highly fragmented following the core development team transition to Amazon
Grok Octo — strong compact open policy but lags frontier generalization/dexterity
By model
ChatGPT
- 1.NVIDIA Isaac GR00T N1.7
- 2.Gemini Robotics 1.5
- 3.Physical Intelligence π0.5
- 4.Figure Helix 02
- 5.Skild Brain
Claude
- 1.π0.5
- 2.Gemini Robotics 1.5
- 3.NVIDIA Isaac GR00T N1.5
- 4.OpenVLA-OFT
- 5.SmolVLA
Gemini
- 1.OpenVLA
- 2.π0
- 3.NVIDIA Isaac GR00T
- 4.Octo
- 5.Skild Brain
Grok
- 1.NVIDIA Isaac GR00T N-Series
- 2.Physical Intelligence π0 / π0.7
- 3.Figure AI Helix
- 4.Google DeepMind Gemini Robotics 1.5
- 5.OpenVLA
This ranking moves
We re-poll all four models weekly. Get one short email when a #1 flips.
Tracked by ModelsAgree · rank 1 = 5 pts … rank 5 = 1 pt · re-polled weekly