# OpenVINO™ Supported Models

The OpenVINO™ toolkit supports most TensorFlow and PyTorch models. The following table lists deep-learning models commonly used in Humanoid Toolkit solutions, and information on how to run them on Intel platforms:

For Humanoid workflows, complete the [platform getting-started guide](../../../platform_foundation/getting_started.md) before installing model dependencies or running these tutorials.

| Algorithm     | Description                                                                                                                         | Link                                                                                                                                                                                                         |
|---------------|-------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| YOLOv8        | CNN-based object detection                                                                                                          | [YOLOv8](https://github.com/openvinotoolkit/openvino_notebooks/tree/2026.2/notebooks/yolov8-optimization)                                                                                                    |
| YOLOv12       | CNN-based object detection                                                                                                          | [YOLOv12](https://github.com/openvinotoolkit/openvino_notebooks/tree/2026.2/notebooks/yolov12-optimization)                                                                                                  |
| MobileNetV2   | CNN-based object detection                                                                                                          | [MobileNetV2](https://github.com/openvinotoolkit/open_model_zoo/tree/master/models/public/mobilenet-v2-1.0-224)                                                                                              |
| SAM           | Transformer-based segmentation                                                                                                      | [SAM](https://github.com/openvinotoolkit/openvino_notebooks/tree/2026.2/notebooks/segment-anything)                                                                                                          |
| SAM2          | Extends SAM to video segmentation and object tracking with cross attention to memory                                                | [SAM2](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/sam2-image-segmentation)                                                                                                  |
| FastSAM       | Lightweight substitute to SAM                                                                                                       | [FastSAM](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/fast-segment-anything)                                                                                                 |
| MobileSAM     | Lightweight substitute to SAM (Same model architecture as SAM. See OpenVINO™ SAM tutorials for model export and application)         | [MobileSAM](https://github.com/openvinotoolkit/openvino_notebooks/tree/2026.2/notebooks/segment-anything)                                                                                                    |
| U-NET         | CNN-based segmentation and diffusion model                                                                                          | [U-NET](https://community.intel.com/t5/Blogs/Products-and-Solutions/Healthcare/Optimizing-Brain-Tumor-Segmentation-BTS-U-Net-model-using-Intel/post/1399037?wapkw=U-Net)                                     |
| DETR          | Transformer-based object detection                                                                                                  | [DETR](https://github.com/openvinotoolkit/open_model_zoo/tree/master/models/public/detr-resnet50)                                                                                                            |
| GroundingDino | Transformer-based object detection                                                                                                  | [GroundingDino](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/grounded-segment-anything)                                                                                       |
| CLIP          | Transformer-based image classification                                                                                              | [CLIP](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/clip-zero-shot-image-classification)                                                                                      |
| Qwen2.5VL     | Multimodal large language model                                                                                                     | [Qwen2.5VL](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks)                                                                                                                     |
| Whisper       | Automatic speech recognition                                                                                                        | [Whisper](https://github.com/openvinotoolkit/openvino_notebooks/tree/latest/notebooks/whisper-asr-genai)                                                                                                     |
| FunASR        | Automatic speech recognition                                                                                                        | [FunASR Setup in LLM Robotics - sample pipeline](../../../software_references/humanoid/sample_pipelines/llm_robotics.md#funasr-setup)                                                                     |

> **Attention:**
  When following these tutorials for model conversion, ensure that the OpenVINO™ toolkit version used for model conversion is the same as the runtime version used for inference. Otherwise, unexpected errors may occur, especially if the model is converted using a newer version and the runtime is an older version. See details in [Troubleshooting](../../../resources/troubleshooting.md).

Please also find information for the models of imitation learning, grasp generation, simultaneous localization and mapping (SLAM) and bird's-eye view (BEV):


:::{toctree}
:maxdepth: 1

model_act
model_cns
model_dp
model_idp3
model_superpoint
model_lightglue
model_fastbev
model_depthanythingv2
model_rdt
model_gr00t_n1d7
:::