smolvla_rubik_pickup_v4 is an open-source robotics policy model designed for automating Rubik's Cube pick-and-place tasks. Below are 17 other ai apps with similar functionality to Smolvla Rubik Pickup, matched by what each product actually does — not ranked or scored. Explore each to find the closest fit for your use case.
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_mobile_robot_lift_pick_up_cube_single is an open-source robotics policy model for mobile robots, enabling pick-and-place tasks. Distributed as an adapter compatible with LeRobot, it supports local fine-tuning and integration into robotics workflows.
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_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_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_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 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.
cube-to-cup-smolvla is an open-source robotics policy model designed for controlling robots in pick-and-place scenarios. It integrates with the LeRobot library and can be installed via pip, supporting robotics researchers and developers in automating manipulation tasks. The model is distributed under an open license for flexible use.
smolvla_so101_pick_place_v5_20k is an open-source vision-language-action model designed for robotic pick-and-place tasks. It integrates with LeRobot and supports policy training and evaluation for robotics researchers.
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_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 DS3 1B1O FV Removeidle Rand40 is a model available on Hugging Face, associated with the robotics domain. The model is referenced in connection with LeRobot, and instructions are provided for using it with this library. The evidence indicates that users can clone the LeRobot repository, install it with a specific option for smolvla, and launch finetuning of the model on a dataset using a provided script. The example given uses a dataset identified as lerobot/svla_so101_pickplace, and allows configuration of batch size, training steps, output directory, job name, device, and integration with wandb for tracking. The model is distributed under the Apache 2.0 license, and is available in the safetensors format. There is also a reference to arxiv: 2506.01844, suggesting a related publication. The evidence does not provide further details about the model's specific capabilities, intended audience beyond robotics and LeRobot users, or additional features. Pricing information is not mentioned, but the Apache 2.0 license indicates it is open source. No claims are made about integrations beyond LeRobot, nor about supported platforms other than those implied by the use of Python scripts and CUDA devices.
act_so101_rubik_v4 is an open-source imitation learning model for robotics, trained to predict action chunks from teleoperated data. It can be deployed locally via LeRobot or CLI tools, supporting robotics researchers in developing advanced robot behaviors.
act_so101_rubik_v2 is an open-source robotics policy based on imitation learning and action chunking with transformers. It enables robots to learn and perform complex tasks by predicting short action sequences from teleoperated data. The model is suitable for robotics researchers and developers seeking advanced control policies.
smolvla_DS3_1B1O_FV_removeidle_rand80 is an open-source robotics policy model designed for use with LeRobot and similar frameworks. It provides pretrained weights and supports local inference and fine-tuning for robotics control tasks. Ideal for robotics researchers and developers seeking customizable policy models.
SmolVla_pick_the_ball is an open-source robotics policy model designed for pick-and-place tasks. It integrates with the LeRobot framework and can be installed via pip for use in robotics research and automation projects. The model is distributed under the Apache-2.0 license and is suitable for developers and researchers in robotics.
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.
