# RT-DETRv4-X

> RT-DETRv4-X: transformer object detector from the RT-DETRv4 family. Available in LibreYOLO, the MIT-licensed open-source library (free for commercial use).

- Family: RT-DETRv4 (Intellindust AI Lab)
- Parameters: 62.0M
- GFLOPs: 202.0
- Default input size: 640px
- Detection: detr · nms-free
- Architecture: transformer · HGNetv2 backbone
- Weight license: Apache-2.0
- Paper-reported mAP@50-95: 57%
- Paper: https://arxiv.org/abs/2510.25257
- Original code: https://arxiv.org/abs/2510.25257

## Benchmarks (COCO val2017)

| Hardware | Runtime | mAP@50-95 | FPS | Latency (ms) | VRAM (MB) |
|---|---|---|---|---|---|
| NVIDIA Jetson Orin Nano Super 8GB | ONNX Runtime FP32 | 60.0 | 2.9 | 342.2 | - |
| NVIDIA Jetson Orin Nano Super 8GB | PyTorch FP32 | 60.0 | 2.8 | 351.8 | 399 |
| NVIDIA Jetson Orin Nano Super 8GB | TensorRT FP16 | 60.0 | 13.8 | 72.7 | - |
| NVIDIA Jetson Orin Nano Super 8GB | TensorRT FP32 | 60.0 | 7.8 | 128.3 | - |
| NVIDIA RTX 5070 Ti | ONNX Runtime FP32 | 60.0 | 38.3 | 26.1 | - |
| NVIDIA RTX 5070 Ti | PyTorch FP32 | 60.0 | 16.6 | 60.1 | 404 |
| NVIDIA RTX 5070 Ti | TensorRT FP16 | 60.0 | 71.0 | 14.1 | - |
| NVIDIA RTX 5070 Ti | TensorRT FP32 | 60.0 | 58.3 | 17.1 | - |
| Raspberry Pi 5 | ONNX Runtime FP32 | 60.0 | 0.4 | 2685.7 | - |

## Usage with LibreYOLO

```python
from libreyolo import LibreYOLO

model = LibreYOLO("LibreRTDETRv4x.pt")
result = model("image.jpg", conf=0.25, iou=0.45)
```

Source: https://www.visionanalysis.org/model/rtdetrv4-x. Benchmarks produced with LibreYOLO (https://github.com/Libre-YOLO/libreyolo).