# Model Preparation & Conversion

AI models are often portable and may be easily adapted to different frameworks. With
[OpenVINO](https://docs.openvino.ai/), the main Open Edge Platform solution for inference and
preparation of pre-trained models, you can easily use **PyTorch, TensorFlow, TensorFlow Lite, ONNX, PaddlePaddle, and JAX/Flax** (experimental).
For best compatibility and performance, it also offers its own format:
[OpenVINO IR](https://docs.openvino.ai/2025/documentation/openvino-ir-format.html).

This means that applications using TensorRT, Triton, or DeepStream can be often ported to
Intel equivalents with minimal effort, opening new possibilities for you to benefit from a
software ecosystem optimized for Intel hardware, including CPUs, GPUs, VPUs, and FPGAs.

To learn more about supported model formats and conversion options, see the OpenVINO guides:
- [Conventional Model Preparation](https://docs.openvino.ai/2025/openvino-workflow/model-preparation.html)
- [Generative Model Preparation](https://docs.openvino.ai/2025/openvino-workflow-generative/genai-model-preparation.html)


You can also **finetune and train** vision-based models to meet your specific needs using
[Geti](https://www.intel.com/content/www/us/en/developer/tools/tiber/edge-platform/model-builder.html).
Offering an intuitive User Interface, it enables you to easily teach the model to recognize
your items or even create a new model from scratch. Simply add image or video data and
annotate it. Geti will export a new version, ready for optimization and deployment. It is
equipped with state-of-the-art technology such as active learning, task chaining, and smart
annotations, to make the labor-intensive tasks, even easier and faster.

For more information, see [Geti Documentation](https://docs.geti.intel.com/).

![model lifecycle](../images/model-lifecycle-infinity-dark.png)




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## Conversion from TAO (.tlt)

Conversion from TAO is not supported by OpenVINO directly. To use TAO models, you need to
export them to ONNX. To see how to migrate from TAO, see the article on
[TAO migration](./migrate-from-tao.md)