OnePlus CPH2573
Geekbench ML Score
927
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 01 2024 09:10 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
554
103.6 IPS |
|
|
Image Classification (F16)
|
100% |
593
111.0 IPS |
|
|
Image Classification (I8)
|
99% |
495
92.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
798
13.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
1022
17.1 IPS |
|
|
Image Segmentation (I8)
|
98% |
949
15.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
1062
1.29 IPS |
|
|
Pose Estimation (F16)
|
100% |
2491
3.02 IPS |
|
|
Pose Estimation (I8)
|
100% |
2489
3.01 IPS |
|
|
Object Detection (F32)
|
100% |
285
21.3 IPS |
|
|
Object Detection (F16)
|
100% |
277
20.6 IPS |
|
|
Object Detection (I8)
|
62% |
272
20.3 IPS |
|
|
Face Detection (F32)
|
100% |
2580
30.7 IPS |
|
|
Face Detection (F16)
|
97% |
2642
31.4 IPS |
|
|
Face Detection (I8)
|
86% |
1701
20.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
1817
14.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
3673
28.5 IPS |
|
|
Depth Estimation (I8)
|
95% |
3673
28.5 IPS |
|
|
Style Transfer (F32)
|
100% |
6549
8.61 IPS |
|
|
Style Transfer (F16)
|
100% |
7854
10.3 IPS |
|
|
Style Transfer (I8)
|
98% |
7705
10.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
413
14.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1212
43.3 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
651
23.2 IPS |
|
|
Text Classification (F32)
|
100% |
145
208.5 IPS |
|
|
Text Classification (F16)
|
100% |
145
208.3 IPS |
|
|
Text Classification (I8)
|
92% |
239
343.5 IPS |
|
|
Machine Translation (F32)
|
100% |
281
5.17 IPS |
|
|
Machine Translation (F16)
|
100% |
281
5.18 IPS |
|
|
Machine Translation (I8)
|
64% |
409
7.53 IPS |
