OnePlus CPH2647
Geekbench ML Score
1141
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | December 18 2024 04:43 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% |
581
108.7 IPS |
|
|
Image Classification (F16)
|
100% |
593
111.0 IPS |
|
|
Image Classification (I8)
|
97% |
967
181.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
740
12.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
753
12.6 IPS |
|
|
Image Segmentation (I8)
|
98% |
703
11.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
1507
1.83 IPS |
|
|
Pose Estimation (F16)
|
100% |
1482
1.79 IPS |
|
|
Pose Estimation (I8)
|
100% |
5864
7.10 IPS |
|
|
Object Detection (F32)
|
100% |
579
43.2 IPS |
|
|
Object Detection (F16)
|
100% |
580
43.3 IPS |
|
|
Object Detection (I8)
|
61% |
1089
81.3 IPS |
|
|
Face Detection (F32)
|
100% |
1342
16.0 IPS |
|
|
Face Detection (F16)
|
100% |
1337
15.9 IPS |
|
|
Face Detection (I8)
|
86% |
2131
25.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
1427
11.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
1406
10.9 IPS |
|
|
Depth Estimation (I8)
|
95% |
2325
18.0 IPS |
|
|
Style Transfer (F32)
|
100% |
2615
3.44 IPS |
|
|
Style Transfer (F16)
|
100% |
2554
3.36 IPS |
|
|
Style Transfer (I8)
|
98% |
5451
7.17 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
909
32.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
978
34.9 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2196
78.4 IPS |
|
|
Text Classification (F32)
|
100% |
560
804.3 IPS |
|
|
Text Classification (F16)
|
100% |
511
734.7 IPS |
|
|
Text Classification (I8)
|
92% |
487
700.2 IPS |
|
|
Machine Translation (F32)
|
100% |
1032
19.0 IPS |
|
|
Machine Translation (F16)
|
100% |
1027
18.9 IPS |
|
|
Machine Translation (I8)
|
64% |
447
8.23 IPS |
