OnePlus CPH2647
Geekbench ML Score
1037
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | December 18 2024 04:48 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
596
111.5 IPS |
|
|
Image Classification (F16)
|
100% |
728
136.2 IPS |
|
|
Image Classification (I8)
|
99% |
626
117.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
799
13.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
1049
17.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
852
14.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
1069
1.29 IPS |
|
|
Pose Estimation (F16)
|
100% |
2487
3.01 IPS |
|
|
Pose Estimation (I8)
|
100% |
2475
3.00 IPS |
|
|
Object Detection (F32)
|
100% |
254
19.0 IPS |
|
|
Object Detection (F16)
|
100% |
273
20.4 IPS |
|
|
Object Detection (I8)
|
62% |
267
19.9 IPS |
|
|
Face Detection (F32)
|
100% |
2665
31.7 IPS |
|
|
Face Detection (F16)
|
97% |
3649
43.4 IPS |
|
|
Face Detection (I8)
|
86% |
3035
36.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
1845
14.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
3760
29.2 IPS |
|
|
Depth Estimation (I8)
|
95% |
3769
29.2 IPS |
|
|
Style Transfer (F32)
|
100% |
5302
6.97 IPS |
|
|
Style Transfer (F16)
|
100% |
7886
10.4 IPS |
|
|
Style Transfer (I8)
|
98% |
7846
10.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
417
14.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
463
16.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
455
16.2 IPS |
|
|
Text Classification (F32)
|
100% |
336
483.4 IPS |
|
|
Text Classification (F16)
|
100% |
340
488.7 IPS |
|
|
Text Classification (I8)
|
92% |
549
788.6 IPS |
|
|
Machine Translation (F32)
|
100% |
530
9.76 IPS |
|
|
Machine Translation (F16)
|
100% |
530
9.74 IPS |
|
|
Machine Translation (I8)
|
64% |
325
5.98 IPS |
