OnePlus CPH2647
Geekbench ML Score
1156
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | December 18 2024 04:45 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | OnePlus CPH2647 |
| Model ID | OnePlus CPH2647 |
| 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 | 10.99 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
586
109.7 IPS |
|
|
Image Classification (F16)
|
100% |
590
110.3 IPS |
|
|
Image Classification (I8)
|
97% |
927
173.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
769
12.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
766
12.8 IPS |
|
|
Image Segmentation (I8)
|
98% |
686
11.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
1505
1.82 IPS |
|
|
Pose Estimation (F16)
|
100% |
1440
1.74 IPS |
|
|
Pose Estimation (I8)
|
100% |
5737
6.95 IPS |
|
|
Object Detection (F32)
|
100% |
595
44.4 IPS |
|
|
Object Detection (F16)
|
100% |
588
43.9 IPS |
|
|
Object Detection (I8)
|
61% |
1108
82.7 IPS |
|
|
Face Detection (F32)
|
100% |
1325
15.7 IPS |
|
|
Face Detection (F16)
|
100% |
1343
16.0 IPS |
|
|
Face Detection (I8)
|
86% |
2241
26.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
1425
11.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
1410
10.9 IPS |
|
|
Depth Estimation (I8)
|
95% |
2416
18.7 IPS |
|
|
Style Transfer (F32)
|
100% |
2650
3.49 IPS |
|
|
Style Transfer (F16)
|
100% |
2567
3.38 IPS |
|
|
Style Transfer (I8)
|
98% |
5857
7.70 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
950
33.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
945
33.7 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2172
77.6 IPS |
|
|
Text Classification (F32)
|
100% |
594
853.7 IPS |
|
|
Text Classification (F16)
|
100% |
656
942.3 IPS |
|
|
Text Classification (I8)
|
92% |
464
667.3 IPS |
|
|
Machine Translation (F32)
|
100% |
1018
18.7 IPS |
|
|
Machine Translation (F16)
|
100% |
1009
18.6 IPS |
|
|
Machine Translation (I8)
|
64% |
454
8.35 IPS |
