OnePlus CPH2573
Geekbench ML Score
261
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 01 2024 09:16 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 | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
113
21.2 IPS |
|
|
Image Classification (F16)
|
100% |
113
21.1 IPS |
|
|
Image Classification (I8)
|
97% |
280
52.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
183
3.06 IPS |
|
|
Image Segmentation (F16)
|
100% |
148
2.47 IPS |
|
|
Image Segmentation (I8)
|
98% |
296
4.95 IPS |
|
|
Pose Estimation (F32)
|
100% |
188
0.23 IPS |
|
|
Pose Estimation (F16)
|
100% |
190
0.23 IPS |
|
|
Pose Estimation (I8)
|
100% |
726
0.88 IPS |
|
|
Object Detection (F32)
|
100% |
114
8.49 IPS |
|
|
Object Detection (F16)
|
100% |
118
8.83 IPS |
|
|
Object Detection (I8)
|
61% |
322
24.1 IPS |
|
|
Face Detection (F32)
|
100% |
338
4.02 IPS |
|
|
Face Detection (F16)
|
100% |
338
4.02 IPS |
|
|
Face Detection (I8)
|
86% |
650
7.72 IPS |
|
|
Depth Estimation (F32)
|
100% |
267
2.07 IPS |
|
|
Depth Estimation (F16)
|
100% |
267
2.07 IPS |
|
|
Depth Estimation (I8)
|
95% |
709
5.50 IPS |
|
|
Style Transfer (F32)
|
100% |
474
0.62 IPS |
|
|
Style Transfer (F16)
|
100% |
474
0.62 IPS |
|
|
Style Transfer (I8)
|
98% |
1307
1.72 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
132
4.71 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
131
4.68 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
448
16.0 IPS |
|
|
Text Classification (F32)
|
100% |
145
208.1 IPS |
|
|
Text Classification (F16)
|
100% |
145
208.2 IPS |
|
|
Text Classification (I8)
|
92% |
237
340.2 IPS |
|
|
Machine Translation (F32)
|
100% |
281
5.17 IPS |
|
|
Machine Translation (F16)
|
100% |
281
5.17 IPS |
|
|
Machine Translation (I8)
|
64% |
317
5.84 IPS |
