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Update NVIDIA Jetson Orin NX 16GB benchmarks with YOLO26 (#24118)

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Lakshantha Dissanayake 2026-04-02 20:32:44 -07:00 committed by GitHub
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docs/en/guides/nvidia-jetson.md
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@ -422,7 +422,7 @@ Even though all model exports work on NVIDIA Jetson, we have only included **PyT
<figure style="text-align: center;">
<img src="https://cdn.jsdelivr.net/gh/ultralytics/assets@main/docs/jetson-orin-nx-16-benchmarks-coco128.avif" alt="Jetson Orin NX 16GB Benchmarks">
<figcaption style="font-style: italic; color: gray;">Benchmarked with Ultralytics 8.3.157</figcaption>
<figcaption style="font-style: italic; color: gray;">Benchmarked with Ultralytics 8.4.33</figcaption>
</figure>
### Detailed Comparison Tables
@ -714,92 +714,92 @@ The below table represents the benchmark results for five different models (YOLO
!!! tip "Performance"
=== "YOLO11n"
=== "YOLO26n"
| Format | Status | Size on disk (MB) | mAP50-95(B) | Inference time (ms/im) |
|-----------------|--------|-------------------|-------------|------------------------|
| PyTorch | ✅ | 5.4 | 0.5101 | 12.90 |
| TorchScript | ✅ | 10.5 | 0.5082 | 13.17 |
| ONNX | ✅ | 10.2 | 0.5081 | 15.43 |
| OpenVINO | ✅ | 10.4 | 0.5058 | 39.80 |
| TensorRT (FP32) | ✅ | 11.8 | 0.5081 | 7.94 |
| TensorRT (FP16) | ✅ | 8.1 | 0.5085 | 4.73 |
| TensorRT (INT8) | ✅ | 5.4 | 0.4786 | 3.90 |
| TF SavedModel | ✅ | 25.9 | 0.5077 | 88.48 |
| TF GraphDef | ✅ | 10.3 | 0.5077 | 86.67 |
| TF Lite | ✅ | 10.3 | 0.5077 | 302.55 |
| MNN | ✅ | 10.1 | 0.5059 | 52.73 |
| NCNN | ✅ | 10.2 | 0.5031 | 32.04 |
| PyTorch | ✅ | 5.3 | 0.4799 | 13.90 |
| TorchScript | ✅ | 9.8 | 0.4787 | 11.60 |
| ONNX | ✅ | 9.5 | 0.4763 | 14.18 |
| OpenVINO | ✅ | 9.6 | 0.4819 | 40.19 |
| TensorRT (FP32) | ✅ | 11.4 | 0.4770 | 7.01 |
| TensorRT (FP16) | ✅ | 8.0 | 0.4789 | 4.13 |
| TensorRT (INT8) | ✅ | 5.5 | 0.4489 | 3.49 |
| TF SavedModel | ✅ | 24.6 | 0.4764 | 92.34 |
| TF GraphDef | ✅ | 9.5 | 0.4764 | 92.06 |
| TF Lite | ✅ | 9.9 | 0.4764 | 254.43 |
| MNN | ✅ | 9.4 | 0.4760 | 48.55 |
| NCNN | ✅ | 9.3 | 0.4805 | 34.31 |
=== "YOLO11s"
=== "YOLO26s"
| Format | Status | Size on disk (MB) | mAP50-95(B) | Inference time (ms/im) |
|-----------------|--------|-------------------|-------------|------------------------|
| PyTorch | ✅ | 18.4 | 0.5790 | 21.70 |
| TorchScript | ✅ | 36.5 | 0.5781 | 22.71 |
| ONNX | ✅ | 36.3 | 0.5781 | 26.49 |
| OpenVINO | ✅ | 36.4 | 0.5810 | 84.73 |
| TensorRT (FP32) | ✅ | 37.8 | 0.5783 | 13.77 |
| TensorRT (FP16) | ✅ | 21.2 | 0.5796 | 7.31 |
| TensorRT (INT8) | ✅ | 12.0 | 0.5735 | 5.33 |
| TF SavedModel | ✅ | 91.0 | 0.5782 | 185.06 |
| TF GraphDef | ✅ | 36.4 | 0.5782 | 186.45 |
| TF Lite | ✅ | 36.3 | 0.5782 | 882.58 |
| MNN | ✅ | 36.2 | 0.5775 | 126.36 |
| NCNN | ✅ | 36.2 | 0.5784 | 66.73 |
| PyTorch | ✅ | 19.5 | 0.5738 | 20.40 |
| TorchScript | ✅ | 36.8 | 0.5664 | 19.20 |
| ONNX | ✅ | 36.5 | 0.5664 | 24.35 |
| OpenVINO | ✅ | 36.7 | 0.5653 | 88.18 |
| TensorRT (FP32) | ✅ | 38.5 | 0.5664 | 12.62 |
| TensorRT (FP16) | ✅ | 21.5 | 0.5652 | 6.41 |
| TensorRT (INT8) | ✅ | 12.6 | 0.5468 | 4.78 |
| TF SavedModel | ✅ | 92.2 | 0.5665 | 195.16 |
| TF GraphDef | ✅ | 36.5 | 0.5665 | 197.57 |
| TF Lite | ✅ | 36.9 | 0.5665 | 827.48 |
| MNN | ✅ | 36.4 | 0.5649 | 123.47 |
| NCNN | ✅ | 36.4 | 0.5697 | 74.04 |
=== "YOLO11m"
=== "YOLO26m"
| Format | Status | Size on disk (MB) | mAP50-95(B) | Inference time (ms/im) |
|-----------------|--------|-------------------|-------------|------------------------|
| PyTorch | ✅ | 38.8 | 0.6266 | 45.00 |
| TorchScript | ✅ | 77.3 | 0.6307 | 51.87 |
| ONNX | ✅ | 76.9 | 0.6307 | 56.00 |
| OpenVINO | ✅ | 77.1 | 0.6284 | 202.69 |
| TensorRT (FP32) | ✅ | 78.7 | 0.6305 | 30.38 |
| TensorRT (FP16) | ✅ | 41.8 | 0.6302 | 14.48 |
| TensorRT (INT8) | ✅ | 23.2 | 0.6291 | 9.74 |
| TF SavedModel | ✅ | 192.7 | 0.6307 | 445.58 |
| TF GraphDef | ✅ | 77.1 | 0.6307 | 460.94 |
| TF Lite | ✅ | 77.0 | 0.6307 | 2653.65 |
| MNN | ✅ | 76.8 | 0.6308 | 339.38 |
| NCNN | ✅ | 76.8 | 0.6284 | 187.64 |
| PyTorch | ✅ | 42.2 | 0.6237 | 38.60 |
| TorchScript | ✅ | 78.5 | 0.6227 | 40.50 |
| ONNX | ✅ | 78.2 | 0.6225 | 48.87 |
| OpenVINO | ✅ | 78.3 | 0.6186 | 205.69 |
| TensorRT (FP32) | ✅ | 80.1 | 0.6217 | 24.69 |
| TensorRT (FP16) | ✅ | 42.6 | 0.6225 | 11.66 |
| TensorRT (INT8) | ✅ | 23.4 | 0.5817 | 8.22 |
| TF SavedModel | ✅ | 196.3 | 0.6229 | 451.48 |
| TF GraphDef | ✅ | 78.2 | 0.6229 | 460.94 |
| TF Lite | ✅ | 78.5 | 0.6229 | 2555.53 |
| MNN | ✅ | 78.0 | 0.6217 | 333.33 |
| NCNN | ✅ | 78.0 | 0.6224 | 214.60 |
=== "YOLO11l"
=== "YOLO26l"
| Format | Status | Size on disk (MB) | mAP50-95(B) | Inference time (ms/im) |
|-----------------|--------|-------------------|-------------|------------------------|
| PyTorch | ✅ | 49.0 | 0.6364 | 56.60 |
| TorchScript | ✅ | 97.6 | 0.6409 | 66.72 |
| ONNX | ✅ | 97.0 | 0.6399 | 71.92 |
| OpenVINO | ✅ | 97.3 | 0.6378 | 254.17 |
| TensorRT (FP32) | ✅ | 99.2 | 0.6406 | 38.89 |
| TensorRT (FP16) | ✅ | 51.9 | 0.6363 | 18.59 |
| TensorRT (INT8) | ✅ | 30.9 | 0.6207 | 12.60 |
| TF SavedModel | ✅ | 243.1 | 0.6409 | 575.98 |
| TF GraphDef | ✅ | 97.2 | 0.6409 | 583.79 |
| TF Lite | ✅ | 97.1 | 0.6409 | 3353.41 |
| MNN | ✅ | 96.9 | 0.6367 | 421.33 |
| NCNN | ✅ | 96.9 | 0.6364 | 228.26 |
| PyTorch | ✅ | 50.7 | 0.6258 | 48.60 |
| TorchScript | ✅ | 95.5 | 0.6249 | 51.60 |
| ONNX | ✅ | 95.0 | 0.6247 | 61.95 |
| OpenVINO | ✅ | 95.3 | 0.6238 | 272.47 |
| TensorRT (FP32) | ✅ | 97.1 | 0.6250 | 31.64 |
| TensorRT (FP16) | ✅ | 51.4 | 0.6225 | 14.77 |
| TensorRT (INT8) | ✅ | 30.0 | 0.5923 | 10.49 |
| TF SavedModel | ✅ | 238.4 | 0.6245 | 596.46 |
| TF GraphDef | ✅ | 95.0 | 0.6245 | 606.10 |
| TF Lite | ✅ | 95.4 | 0.6245 | 3275.55 |
| MNN | ✅ | 94.8 | 0.6247 | 408.15 |
| NCNN | ✅ | 94.8 | 0.6323 | 262.99 |
=== "YOLO11x"
=== "YOLO26x"
| Format | Status | Size on disk (MB) | mAP50-95(B) | Inference time (ms/im) |
|-----------------|--------|-------------------|-------------|------------------------|
| PyTorch | ✅ | 109.3 | 0.7005 | 98.50 |
| TorchScript | ✅ | 218.1 | 0.6901 | 123.03 |
| ONNX | ✅ | 217.5 | 0.6901 | 129.55 |
| OpenVINO | ✅ | 217.8 | 0.6876 | 483.44 |
| TensorRT (FP32) | ✅ | 219.6 | 0.6904 | 75.92 |
| TensorRT (FP16) | ✅ | 112.1 | 0.6885 | 35.78 |
| TensorRT (INT8) | ✅ | 61.6 | 0.6592 | 21.60 |
| TF SavedModel | ✅ | 544.3 | 0.6900 | 1120.43 |
| TF GraphDef | ✅ | 217.7 | 0.6900 | 1172.35 |
| TF Lite | ✅ | 217.6 | 0.6900 | 7283.63 |
| MNN | ✅ | 217.3 | 0.6877 | 840.16 |
| NCNN | ✅ | 217.3 | 0.6849 | 474.41 |
| PyTorch | ✅ | 113.2 | 0.6561 | 84.40 |
| TorchScript | ✅ | 213.5 | 0.6594 | 91.20 |
| ONNX | ✅ | 212.9 | 0.6595 | 109.34 |
| OpenVINO | ✅ | 213.2 | 0.6592 | 520.88 |
| TensorRT (FP32) | ✅ | 215.1 | 0.6593 | 57.18 |
| TensorRT (FP16) | ✅ | 109.7 | 0.6632 | 26.76 |
| TensorRT (INT8) | ✅ | 60.0 | 0.6170 | 17.32 |
| TF SavedModel | ✅ | 533.3 | 0.6593 | 1170.50 |
| TF GraphDef | ✅ | 212.9 | 0.6593 | 1217.87 |
| TF Lite | ✅ | 213.3 | 0.6593 | 7247.11 |
| MNN | ✅ | 212.8 | 0.6591 | 820.90 |
| NCNN | ✅ | 212.8 | 0.6666 | 534.30 |
Benchmarked with Ultralytics 8.3.157
Benchmarked with Ultralytics 8.4.33
!!! note