cube-to-cup-smolvla is an open-source robotics policy model designed for controlling robots in pick-and-place scenarios. Below are 15 other ai apps with similar functionality to Cube To Cup Smolvla, matched by what each product actually does — not ranked or scored. Explore each to find the closest fit for your use case.
Cube To Cup Act is a robotics policy model based on imitation learning, designed to predict short sequences of actions—referred to as action chunks—rather than single-step actions. This approach enables the model to learn from teleoperated data and is intended to achieve high success rates in robotic tasks. The model has been trained and made available through the Hugging Face Hub, and it is associated with the LeRobot library, which provides guidance on training and deploying the policy. The tool is delivered as a model that can be used with various libraries, inference providers, notebooks, and local applications. Specific instructions are provided for integration with LeRobot, and there are resources for running the policy on robots, training custom policies, and evaluating performance. The model card and documentation offer further details on usage and implementation. 0 license, making it available as open-source software. It is positioned within the field of robotics and imitation learning, with a focus on action chunking using transformer-based methods.
smolvla_ball_cup is an open-source robotics policy model for ball-cup sorting tasks, designed for use with the LeRobot framework. It enables robotics researchers and developers to train, fine-tune, and deploy sorting policies in simulation or on real robots.
smolvla_so101_cube_put_20260710_frozen is an open-source robotics policy model designed for cube manipulation tasks. It is compatible with the LeRobot library and can be used for research, training, and evaluation in robotics environments. The model is distributed via Hugging Face for local use and further experimentation.
smolvla_p3_redcube_merged is an open-source robotics policy model designed for manipulation and control tasks. It is suitable for robotics researchers and developers seeking to implement or fine-tune policies for robotic arms and similar systems.
smolvla_so101_cube_put_20260710_frozen_200k is an open-source robotics policy model designed for cube manipulation and pick-and-place tasks. It integrates with LeRobot and is suitable for researchers and developers working on robotic control and imitation learning.
smolvla_so101_cube_put_20260710 is an open-source robotics policy model for cube placement tasks, designed for use with the LeRobot framework. It allows researchers and engineers to train, fine-tune, and deploy robotics policies using open weights.
smolvla_ball_cup_30k is an open-source robotics policy model designed for ball-cup sorting tasks. It integrates with the LeRobot library and can be used for training and running robotics policies in Python environments. The model is intended for robotics researchers and developers working on manipulation tasks.
ball_cup_smolvla_try3_model is an open-source robotics policy model for ball-and-cup manipulation tasks. It is intended for robotics researchers and developers to train, evaluate, and deploy manipulation policies using LeRobot and Python.
Smolvla Wrist Top Cube is a model available on Hugging Face that is associated with robotics applications. The evidence indicates that it is intended for use with the LeRobot library, as instructions are provided for integrating the model into LeRobot workflows. Users are guided to install LeRobot and utilize specific scripts for tasks such as fine-tuning the model on a dataset and running the policy with a robot. The model appears to be distributed in the Safetensors format and is referenced with an arXiv preprint, suggesting a research context. The model is released under the Apache-2.0 license, making it open source. There is no information in the evidence about pricing, so it is not possible to determine whether there are paid plans or restrictions beyond the open-source license. The documentation provides command-line examples for training and running the model, indicating that it is aimed at users familiar with Python and robotics software development. The mention of datasets and batch sizes in the training commands suggests that the model is designed to be fine-tuned or adapted to specific robotic tasks, though the precise nature of these tasks is not detailed in the evidence provided. No specific information is given about the types of robots supported, the exact manipulation tasks addressed, or the intended audience beyond those using LeRobot and Hugging Face infrastructure. The evidence does not mention any integrations beyond LeRobot, nor does it describe the model's performance, supported platforms, or hardware requirements. Overall, Smolvla Wrist Top Cube is positioned as an open-source robotics model for use with LeRobot, with capabilities for training and deployment in compatible environments.
smolvla_so101_cube_put_take_20260710 is an open-source robotics policy model designed for cube put-and-take tasks, compatible with the LeRobot framework. It allows robotics researchers to run, fine-tune, and evaluate manipulation policies in simulation or on real robots.
Smolvla So100 Stack Cube is a model hosted on Hugging Face, categorized under robotics. The evidence indicates that it is associated with LeRobot, a robotics library, and can be used for tasks related to robotics policies. The model is distributed in the safetensors format and is available under the Apache-2.0 license. Users are provided with instructions for integrating the model with LeRobot, including commands for fine-tuning the model on custom datasets and running the policy using the record function. The evidence references an arXiv paper (arxiv: 2506.01844), suggesting a research context, but does not provide further details about the model's architecture or specific use cases. Access is provided via Hugging Face, and the model can be used with various libraries, inference providers, notebooks, and local applications as indicated by the general instructions. No information is provided about pricing, target user roles, or specific capabilities beyond its connection to robotics and LeRobot.
smolvla_so100_stack_cube_v2 is an open-source robotics policy model designed for stacking cube tasks. It integrates with LeRobot and can be used via CLI tools, supporting fine-tuning and research in robotic manipulation.
smolvla_so100_stack_cube_merged is an open-source AI model designed for robotic control and manipulation tasks. It supports vision-language-action integration and can be used by robotics researchers and developers for automation and experimentation.
smolvla_rubik_pickup_v4 is an open-source robotics policy model designed for automating Rubik's Cube pick-and-place tasks. Distributed via Hugging Face, it can be integrated with robotics frameworks like LeRobot and is suitable for researchers and developers working on robotic manipulation.
smolvla_white_in_blue_circle is an open-source AI model for robotics control and policy learning, distributed with model weights and instructions for use with the LeRobot library. It is intended for robotics researchers and developers building control systems.
