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Update NVIDIA Jetson Orin Nano Super benchmarks with YOLO26 (#24097)
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Lakshantha Dissanayake
GitHub
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1 changed files with 67 additions and 67 deletions
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@ -415,7 +415,7 @@ Even though all model exports work on NVIDIA Jetson, we have only included **PyT
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<figure style="text-align: center;">
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<img src="https://cdn.jsdelivr.net/gh/ultralytics/assets@main/docs/jetson-orin-nano-super-benchmarks-coco128.avif" alt="Jetson Orin Nano Super Benchmarks">
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<figcaption style="font-style: italic; color: gray;">Benchmarked with Ultralytics 8.3.157</figcaption>
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<figcaption style="font-style: italic; color: gray;">Benchmarked with Ultralytics 8.4.33</figcaption>
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</figure>
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#### NVIDIA Jetson Orin NX 16GB
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@ -619,92 +619,92 @@ The below table represents the benchmark results for five different models (YOLO
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!!! tip "Performance"
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=== "YOLO11n"
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=== "YOLO26n"
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| Format | Status | Size on disk (MB) | mAP50-95(B) | Inference time (ms/im) |
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|-----------------|--------|-------------------|-------------|------------------------|
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| PyTorch | ✅ | 5.4 | 0.5101 | 13.70 |
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| TorchScript | ✅ | 10.5 | 0.5082 | 13.69 |
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| ONNX | ✅ | 10.2 | 0.5081 | 14.47 |
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| OpenVINO | ✅ | 10.4 | 0.5058 | 56.66 |
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| TensorRT (FP32) | ✅ | 12.0 | 0.5081 | 7.44 |
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| TensorRT (FP16) | ✅ | 8.2 | 0.5061 | 4.53 |
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| TensorRT (INT8) | ✅ | 5.4 | 0.4825 | 3.70 |
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| TF SavedModel | ✅ | 25.9 | 0.5077 | 116.23 |
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| TF GraphDef | ✅ | 10.3 | 0.5077 | 114.92 |
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| TF Lite | ✅ | 10.3 | 0.5077 | 340.75 |
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| MNN | ✅ | 10.1 | 0.5059 | 76.26 |
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| NCNN | ✅ | 10.2 | 0.5031 | 45.03 |
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| PyTorch | ✅ | 5.3 | 0.4790 | 15.60 |
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| TorchScript | ✅ | 9.8 | 0.4770 | 12.60 |
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| ONNX | ✅ | 9.5 | 0.4760 | 15.76 |
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| OpenVINO | ✅ | 9.6 | 0.4820 | 56.23 |
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| TensorRT (FP32) | ✅ | 11.3 | 0.4770 | 7.53 |
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| TensorRT (FP16) | ✅ | 8.1 | 0.4800 | 4.57 |
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| TensorRT (INT8) | ✅ | 5.3 | 0.4490 | 3.80 |
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| TF SavedModel | ✅ | 24.6 | 0.4760 | 118.33 |
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| TF GraphDef | ✅ | 9.5 | 0.4760 | 116.30 |
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| TF Lite | ✅ | 9.9 | 0.4760 | 286.00 |
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| MNN | ✅ | 9.4 | 0.4760 | 68.77 |
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| NCNN | ✅ | 9.3 | 0.4810 | 47.50 |
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=== "YOLO11s"
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=== "YOLO26s"
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| Format | Status | Size on disk (MB) | mAP50-95(B) | Inference time (ms/im) |
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|-----------------|--------|-------------------|-------------|------------------------|
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| PyTorch | ✅ | 18.4 | 0.5790 | 20.90 |
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| TorchScript | ✅ | 36.5 | 0.5781 | 21.22 |
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| ONNX | ✅ | 36.3 | 0.5781 | 25.07 |
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| OpenVINO | ✅ | 36.4 | 0.5810 | 122.98 |
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| TensorRT (FP32) | ✅ | 37.9 | 0.5783 | 13.02 |
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| TensorRT (FP16) | ✅ | 21.8 | 0.5779 | 6.93 |
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| TensorRT (INT8) | ✅ | 12.2 | 0.5735 | 5.08 |
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| TF SavedModel | ✅ | 91.0 | 0.5782 | 250.65 |
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| TF GraphDef | ✅ | 36.4 | 0.5782 | 252.69 |
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| TF Lite | ✅ | 36.3 | 0.5782 | 998.68 |
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| MNN | ✅ | 36.2 | 0.5781 | 188.01 |
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| NCNN | ✅ | 36.2 | 0.5784 | 101.37 |
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| PyTorch | ✅ | 20.0 | 0.5730 | 22.83 |
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| TorchScript | ✅ | 36.8 | 0.5670 | 21.83 |
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| ONNX | ✅ | 36.5 | 0.5664 | 26.29 |
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| OpenVINO | ✅ | 36.7 | 0.5653 | 127.09 |
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| TensorRT (FP32) | ✅ | 38.2 | 0.5664 | 13.60 |
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| TensorRT (FP16) | ✅ | 21.3 | 0.5649 | 7.17 |
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| TensorRT (INT8) | ✅ | 12.7 | 0.5468 | 5.25 |
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| TF SavedModel | ✅ | 92.2 | 0.5665 | 263.69 |
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| TF GraphDef | ✅ | 36.5 | 0.5665 | 268.21 |
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| TF Lite | ✅ | 36.9 | 0.5665 | 949.63 |
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| MNN | ✅ | 36.4 | 0.5644 | 184.68 |
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| NCNN | ✅ | 36.4 | 0.5697 | 107.48 |
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=== "YOLO11m"
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=== "YOLO26m"
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| Format | Status | Size on disk (MB) | mAP50-95(B) | Inference time (ms/im) |
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|-----------------|--------|-------------------|-------------|------------------------|
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| PyTorch | ✅ | 38.8 | 0.6266 | 46.50 |
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| TorchScript | ✅ | 77.3 | 0.6307 | 47.95 |
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| ONNX | ✅ | 76.9 | 0.6307 | 53.06 |
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| OpenVINO | ✅ | 77.1 | 0.6284 | 301.63 |
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| TensorRT (FP32) | ✅ | 78.8 | 0.6305 | 27.86 |
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| TensorRT (FP16) | ✅ | 41.7 | 0.6309 | 13.50 |
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| TensorRT (INT8) | ✅ | 23.2 | 0.6291 | 9.12 |
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| TF SavedModel | ✅ | 192.7 | 0.6307 | 622.24 |
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| TF GraphDef | ✅ | 77.1 | 0.6307 | 628.74 |
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| TF Lite | ✅ | 77.0 | 0.6307 | 2997.93 |
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| MNN | ✅ | 76.8 | 0.6299 | 509.96 |
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| NCNN | ✅ | 76.8 | 0.6284 | 292.99 |
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| PyTorch | ✅ | 43.0 | 0.6220 | 44.43 |
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| TorchScript | ✅ | 78.5 | 0.6230 | 44.00 |
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| ONNX | ✅ | 78.2 | 0.6225 | 53.44 |
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| OpenVINO | ✅ | 78.3 | 0.6186 | 303.26 |
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| TensorRT (FP32) | ✅ | 80.0 | 0.6217 | 28.19 |
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| TensorRT (FP16) | ✅ | 42.6 | 0.6225 | 13.59 |
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| TensorRT (INT8) | ✅ | 23.4 | 0.5817 | 9.30 |
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| TF SavedModel | ✅ | 196.3 | 0.6229 | 636.03 |
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| TF GraphDef | ✅ | 78.2 | 0.6229 | 659.57 |
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| TF Lite | ✅ | 78.5 | 0.6229 | 2905.17 |
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| MNN | ✅ | 78.0 | 0.6168 | 500.09 |
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| NCNN | ✅ | 78.0 | 0.6224 | 332.39 |
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=== "YOLO11l"
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=== "YOLO26l"
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| Format | Status | Size on disk (MB) | mAP50-95(B) | Inference time (ms/im) |
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|-----------------|--------|-------------------|-------------|------------------------|
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| PyTorch | ✅ | 49.0 | 0.6364 | 56.50 |
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| TorchScript | ✅ | 97.6 | 0.6409 | 62.51 |
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| ONNX | ✅ | 97.0 | 0.6399 | 68.35 |
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| OpenVINO | ✅ | 97.3 | 0.6378 | 376.03 |
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| TensorRT (FP32) | ✅ | 99.2 | 0.6396 | 35.59 |
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| TensorRT (FP16) | ✅ | 52.1 | 0.6361 | 17.48 |
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| TensorRT (INT8) | ✅ | 30.9 | 0.6207 | 11.87 |
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| TF SavedModel | ✅ | 243.1 | 0.6409 | 807.47 |
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| TF GraphDef | ✅ | 97.2 | 0.6409 | 822.88 |
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| TF Lite | ✅ | 97.1 | 0.6409 | 3792.23 |
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| MNN | ✅ | 96.9 | 0.6372 | 631.16 |
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| NCNN | ✅ | 96.9 | 0.6364 | 350.46 |
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| PyTorch | ✅ | 51.0 | 0.6230 | 60.97 |
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| TorchScript | ✅ | 95.5 | 0.6250 | 56.20 |
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| ONNX | ✅ | 95.0 | 0.6247 | 68.12 |
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| OpenVINO | ✅ | 95.3 | 0.6238 | 397.84 |
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| TensorRT (FP32) | ✅ | 97.1 | 0.6250 | 35.88 |
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| TensorRT (FP16) | ✅ | 51.4 | 0.6225 | 17.42 |
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| TensorRT (INT8) | ✅ | 30.0 | 0.5923 | 11.83 |
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| TF SavedModel | ✅ | 238.4 | 0.6245 | 835.83 |
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| TF GraphDef | ✅ | 95.0 | 0.6245 | 852.16 |
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| TF Lite | ✅ | 95.4 | 0.6245 | 3650.85 |
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| MNN | ✅ | 94.8 | 0.6257 | 612.37 |
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| NCNN | ✅ | 94.8 | 0.6323 | 405.45 |
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=== "YOLO11x"
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=== "YOLO26x"
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| Format | Status | Size on disk (MB) | mAP50-95(B) | Inference time (ms/im) |
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|-----------------|--------|-------------------|-------------|------------------------|
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| PyTorch | ✅ | 109.3 | 0.7005 | 90.00 |
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| TorchScript | ✅ | 218.1 | 0.6901 | 113.40 |
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| ONNX | ✅ | 217.5 | 0.6901 | 122.94 |
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| OpenVINO | ✅ | 217.8 | 0.6876 | 713.1 |
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| TensorRT (FP32) | ✅ | 219.5 | 0.6904 | 66.93 |
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| TensorRT (FP16) | ✅ | 112.2 | 0.6892 | 32.58 |
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| TensorRT (INT8) | ✅ | 61.5 | 0.6612 | 19.90 |
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| TF SavedModel | ✅ | 544.3 | 0.6900 | 1605.4 |
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| TF GraphDef | ✅ | 217.8 | 0.6900 | 2961.8 |
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| TF Lite | ✅ | 217.6 | 0.6900 | 8234.86 |
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| MNN | ✅ | 217.3 | 0.6893 | 1254.18 |
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| NCNN | ✅ | 217.3 | 0.6849 | 725.50 |
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| PyTorch | ✅ | 113.2 | 0.6561 | 98.44 |
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| TorchScript | ✅ | 214.0 | 0.6593 | 98.0 |
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| ONNX | ✅ | 212.9 | 0.6595 | 122.43 |
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| OpenVINO | ✅ | 213.2 | 0.6592 | 760.72 |
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| TensorRT (FP32) | ✅ | 215.1 | 0.6593 | 67.17 |
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| TensorRT (FP16) | ✅ | 110.2 | 0.6637 | 32.60 |
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| TensorRT (INT8) | ✅ | 59.9 | 0.6170 | 19.99 |
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| TF SavedModel | ✅ | 533.3 | 0.6593 | 1647.06 |
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| TF GraphDef | ✅ | 212.9 | 0.6593 | 1670.30 |
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| TF Lite | ✅ | 213.3 | 0.6590 | 8066.30 |
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| MNN | ✅ | 212.8 | 0.6600 | 1227.90 |
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| NCNN | ✅ | 212.8 | 0.6666 | 782.24 |
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Benchmarked with Ultralytics 8.3.157
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Benchmarked with Ultralytics 8.4.33
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!!! note
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