OnePlus CPH2573
Geekbench ML Score
966
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 01 2024 09:06 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | OnePlus CPH2573 |
| Model ID | OnePlus CPH2573 |
| Motherboard | pineapple |
| Governor | uag |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.26 GHz |
| Cluster 1 | 2 Cores @ 2.27 GHz |
| Cluster 2 | 2 Cores @ 2.96 GHz |
| Cluster 3 | 3 Cores @ 3.15 GHz |
| Cluster 4 | 1 Core @ 3.30 GHz |
| Memory Information | |
|---|---|
| Size | 14.90 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
468
87.5 IPS |
|
|
Image Classification (F16)
|
100% |
473
88.6 IPS |
|
|
Image Classification (I8)
|
97% |
792
148.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
628
10.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
636
10.6 IPS |
|
|
Image Segmentation (I8)
|
98% |
619
10.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
1318
1.60 IPS |
|
|
Pose Estimation (F16)
|
100% |
1330
1.61 IPS |
|
|
Pose Estimation (I8)
|
100% |
4781
5.79 IPS |
|
|
Object Detection (F32)
|
100% |
504
37.6 IPS |
|
|
Object Detection (F16)
|
100% |
513
38.3 IPS |
|
|
Object Detection (I8)
|
61% |
1020
76.2 IPS |
|
|
Face Detection (F32)
|
100% |
1156
13.7 IPS |
|
|
Face Detection (F16)
|
100% |
1148
13.6 IPS |
|
|
Face Detection (I8)
|
86% |
1721
20.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
1087
8.43 IPS |
|
|
Depth Estimation (F16)
|
100% |
1070
8.30 IPS |
|
|
Depth Estimation (I8)
|
95% |
1599
12.4 IPS |
|
|
Style Transfer (F32)
|
100% |
2152
2.83 IPS |
|
|
Style Transfer (F16)
|
100% |
2168
2.85 IPS |
|
|
Style Transfer (I8)
|
98% |
4298
5.65 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
725
25.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
728
26.0 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1753
62.6 IPS |
|
|
Text Classification (F32)
|
100% |
512
736.1 IPS |
|
|
Text Classification (F16)
|
100% |
497
713.8 IPS |
|
|
Text Classification (I8)
|
92% |
371
532.6 IPS |
|
|
Machine Translation (F32)
|
100% |
1153
21.2 IPS |
|
|
Machine Translation (F16)
|
100% |
1149
21.1 IPS |
|
|
Machine Translation (I8)
|
64% |
377
6.94 IPS |
