# Benchmarks

This page provides performance benchmarks for the DeGirum® Orca accelerator across a variety of models. The frames per second (FPS) numbers were generated by running the [single\_model\_performance\_test.ipynb](https://github.com/DeGirum/PySDKExamples/blob/main/examples/benchmarks/single_model_performance_test.ipynb) notebook on an Orca accelerator (ORCA1). You can reproduce these results by running the same notebook locally or in the DeGirum AI Hub. All FPS numbers assume **batch\_size=1**. We update this page periodically as our compiler and software evolve, adding more models and improving performance.

These benchmarks were last updated on Oct 23, 2023.

| Model Name                                 | FPS |
| ------------------------------------------ | :-: |
| efficientnet\_es\_imagenet--224x224\_quant | 187 |
| mobiledet\_coco--320x320\_quant            | 128 |
| mobilenet\_v1\_imagenet--224x224\_quant    | 407 |
| mobilenet\_v2\_imagenet--224x224\_quant    | 360 |
| resnet50\_imagenet--224x224\_pruned\_quant | 250 |
| yolo\_v5s\_face\_det--512x512\_quant       | 126 |


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.degirum.com/orca/benchmarks.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.