> For the complete documentation index, see [llms.txt](https://nx.docs.scailable.net/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://nx.docs.scailable.net/ai-manager-v6.1.4/ai-accelerators-support/introduction-to-oaxs.md).

# Accelerators Overview

The AI Manager accelerates AI model inference using built-in runtimes, each dedicated to a specific platform and AI accelerator (CPU, GPU, NPU, etc.). These runtimes integrate directly into the AI Manager, so new runtimes and acceleration types can be added.

When a user uploads a [supported model](/ai-manager-v6.1.4/ai-models-support/importing-models.md) to the AI Manager Cloud, the platform runs several conversion processes on the file, each generating a model artifact for one of the [runtimes](/ai-manager-v6.1.4/ai-accelerators-support/supported-ai-accelerators.md).

## Example of a Teachable Machine Model

Suppose you've trained a teachable machine model, and exported it according to the guidelines mentioned [here](/ai-manager-v6.1.4/ai-models-support/importing-models/from-teachable-machine.md), the following model artifacts are stored to be used by the AI Manager when needed:

<figure><img src="/files/qZukOHfbFRQAdiuhEn6Z" alt="Model detail page showing available artifact download types: Default ONNX, Original ZIP,
     Hailo 8L ONNX, and Hailo 8 ONNX"><figcaption><p>Model artifact types: each runtime uses a different artifact generated from the uploaded model.</p></figcaption></figure>

* `application/zip; source=original`: is the original ZIP archive that's uploaded in the interface.
* `application/zip; kind=teachable-machine`: is the original ZIP archive that's uploaded in the interface with specific details for Teachable Machine.
* `application/x-onnx`: converts the TFLite generated earlier to ONNX, validated and optimized to run on CPU, Intel, and NVIDIA hardware.\
  *This step does not perform quantization on the model.*
* `application/zip; device=mxa`: is the artifact generated by compiling the ONNX file into an optimized file dedicated only for MemryX hardware.
* `application/x-onnx; device=hailo`: is a custom ONNX generated specifically for Hailo-8 chips.

{% hint style="info" %}
Any runtime or toolchain combination that follows the [Open AI Accelerator eXchange (OAAX)](https://www.oaax.org/) standard is compatible with the AI Manager, so any installed runtime can be swapped for a new one.\
AI chip makers integrating with the AI Manager can refer to the documentation repository on [GitHub](https://github.com/OAAX-standard/OAAX).
{% endhint %}