rockchip orangepi5
Geekbench ML Score
479
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 08 2024 12:41 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | rockchip orangepi5 |
| Model ID | rockchip orangepi5 |
| Motherboard | rk30sdk |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 4 part 3339 revision 0 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 4 Cores @ 2.26 GHz |
| Memory Information | |
|---|---|
| Size | 15.33 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
318
59.4 IPS |
|
|
Image Classification (F16)
|
100% |
454
85.0 IPS |
|
|
Image Classification (I8)
|
97% |
430
80.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
435
7.27 IPS |
|
|
Image Segmentation (F16)
|
100% |
614
10.3 IPS |
|
|
Image Segmentation (I8)
|
98% |
603
10.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
327
0.40 IPS |
|
|
Pose Estimation (F16)
|
100% |
441
0.53 IPS |
|
|
Pose Estimation (I8)
|
100% |
441
0.53 IPS |
|
|
Object Detection (F32)
|
100% |
239
17.8 IPS |
|
|
Object Detection (F16)
|
100% |
332
24.8 IPS |
|
|
Object Detection (I8)
|
62% |
333
24.8 IPS |
|
|
Face Detection (F32)
|
100% |
966
11.5 IPS |
|
|
Face Detection (F16)
|
98% |
1168
13.9 IPS |
|
|
Face Detection (I8)
|
86% |
1096
13.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
653
5.07 IPS |
|
|
Depth Estimation (F16)
|
100% |
743
5.76 IPS |
|
|
Depth Estimation (I8)
|
95% |
737
5.72 IPS |
|
|
Style Transfer (F32)
|
100% |
1512
1.99 IPS |
|
|
Style Transfer (F16)
|
100% |
1807
2.38 IPS |
|
|
Style Transfer (I8)
|
98% |
1799
2.37 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
325
11.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
398
14.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
395
14.1 IPS |
|
|
Text Classification (F32)
|
100% |
158
227.6 IPS |
|
|
Text Classification (F16)
|
100% |
157
225.8 IPS |
|
|
Text Classification (I8)
|
92% |
257
368.7 IPS |
|
|
Machine Translation (F32)
|
100% |
284
5.23 IPS |
|
|
Machine Translation (F16)
|
100% |
289
5.32 IPS |
|
|
Machine Translation (I8)
|
64% |
270
4.98 IPS |
