> For the complete documentation index, see [llms.txt](https://docs.degirum.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.degirum.com/ai-hub/public-models/memryx.md).

# MemryX

This page features models for MemryX devices currently available on the DeGirum AI Hub model zoo.

Models are located at the [MemryX model zoo on the AI Hub](https://hub.degirum.com/public-models/degirum/memryx?utm_source=docs.degirum.com\&utm_medium=site\&utm_campaign=ai-hub-public-models-memryx).

## Models by DeGirum

### MemryX MX3

**Age Estimation**

| Model Name                                          | Use Case       | MAE | MSE |
| --------------------------------------------------- | -------------- | --- | --- |
| yolov8n\_relu6\_age--256x256\_float\_memryx\_mx3\_1 | Age Estimation |     |     |

**Classification**

| Model Name                                                       | Use Case              | Top‑1  | Top‑5   |
| ---------------------------------------------------------------- | --------------------- | ------ | ------- |
| mobilenet\_imagenet--224x224\_float\_memryx\_mx3\_1              | Classification        |        |         |
| mobilenet\_v2\_imagenet--224x224\_float\_memryx\_mx3\_1          | Classification        |        |         |
| resnet50\_imagenet--224x224\_float\_memryx\_mx3\_1               | Classification        |        |         |
| yolov8n\_imagenet--224x224\_float\_memryx\_mx3\_1                | Classification        |        |         |
| yolov8n\_relu6\_fairface\_gender--256x256\_float\_memryx\_mx3\_1 | Gender Classification | 91.18% | 100.00% |
| yolov8s\_imagenet--224x224\_float\_memryx\_mx3\_1                | Classification        |        |         |

**Detection**

| Model Name                                                      | Use Case                           | mAP 50‑95                              | mAP 50                                 |
| --------------------------------------------------------------- | ---------------------------------- | -------------------------------------- | -------------------------------------- |
| yolov5n\_relu6\_coco--640x640\_float\_memryx\_mx3\_1            | COCO Detection                     | 24.61                                  | 41.30                                  |
| yolov5s\_relu6\_coco--640x640\_float\_memryx\_mx3\_1            | COCO Detection                     | 34.90                                  | 53.82                                  |
| yolov5m\_relu6\_coco--640x640\_float\_memryx\_mx3\_1            | COCO Detection                     | 41.99                                  | 60.31                                  |
| yolov8n\_coco--640x640\_float\_memryx\_mx3\_1                   | COCO Detection                     | 0.3693                                 | 0.5223                                 |
| yolov8n\_relu6\_coco--640x640\_float\_memryx\_mx3\_1            | COCO Detection                     | 0.3493                                 | 0.4994                                 |
| yolov8n\_coco\_pose--640x640\_float\_memryx\_mx3\_1             | COCO Pose Keypoints                | <p>bbox: 0.5227</p><p>kpts: 0.4923</p> | <p>bbox: 0.7116</p><p>kpts: 0.7923</p> |
| yolov8n\_coco\_seg--640x640\_float\_memryx\_mx3\_1              | COCO Instance Segmentation         | <p>bbox: 0.3618</p><p>mask: 0.2114</p> | <p>bbox: 0.5155</p><p>mask: 0.4303</p> |
| yolov8n\_relu6\_car--640x640\_float\_memryx\_mx3\_1             | Car Detection                      | 0.6862                                 | 0.8568                                 |
| yolov8n\_relu6\_face--640x640\_float\_memryx\_mx3\_1            | Face Detection                     | 0.5685                                 | 0.7760                                 |
| yolov8n\_relu6\_fire\_smoke--640x640\_float\_memryx\_mx3\_1     | Fire & Smoke Detection             | 0.4151                                 | 0.7415                                 |
| yolov8n\_relu6\_hand--640x640\_float\_memryx\_mx3\_1            | Hand Detection                     | 0.4606                                 | 0.7687                                 |
| yolov8n\_relu6\_human\_head--640x640\_float\_memryx\_mx3\_1     | Head Detection                     | 0.4850                                 | 0.7148                                 |
| yolov8n\_relu6\_lp--640x640\_float\_memryx\_mx3\_1              | License Plate Detection            | 0.5704                                 | 0.8632                                 |
| yolov8n\_relu6\_person--640x640\_float\_memryx\_mx3\_1          | Person Detection                   | 0.3149                                 | 0.5211                                 |
| yolov8n\_relu6\_ppe--640x640\_float\_memryx\_mx3\_1             | PPE Detection                      | 0.3587                                 | 0.6807                                 |
| yolov8n\_relu6\_widerface\_kpts--640x640\_float\_memryx\_mx3\_1 | Face Detection with Five Keypoints | <p>bbox: 0.2717</p><p>kpts: 0.2396</p> | <p>bbox: 0.7977</p><p>kpts: 0.5510</p> |
| yolov8s\_relu6\_widerface\_kpts--640x640\_float\_memryx\_mx3\_1 | Face Detection with Five Keypoints |                                        |                                        |
| yolov8n\_relu6\_coco\_pose--640x640\_float\_memryx\_mx3\_1      | COCO Pose Keypoints                | <p>bbox: 0.5253</p><p>kpts: 0.4530</p> | <p>bbox: 0.7165</p><p>kpts: 0.7830</p> |
| yolov8n\_coco\_seg--640x640\_float\_memryx\_mx3\_1              | COCO Instance Segmentation         | <p>bbox: 0.4255</p><p>mask: 0.3429</p> | <p>bbox: 0.5549</p><p>mask: 0.4930</p> |
| yolov8n\_relu6\_coco\_seg--640x640\_float\_memryx\_mx3\_1       | COCO Instance Segmentation         | <p>bbox: 0.3429</p><p>mask: 0.2826</p> | <p>bbox: 0.4889</p><p>mask: 0.4575</p> |
| yolov8n\_relu6\_coco\_seg--640x640\_float\_memryx\_mx3\_1       | COCO Instance Segmentation         | <p>bbox: 0.3414</p><p>mask: 0.2080</p> | <p>bbox: 0.4875</p><p>mask: 0.4133</p> |