OnePlus CPH2569
Geekbench ML Score
396
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 21 2024 03:20 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | OnePlus CPH2569 |
| Model ID | OnePlus CPH2569 |
| Motherboard | lahaina |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 1 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.40 GHz |
| Cluster 3 | 1 Core @ 2.71 GHz |
| Memory Information | |
|---|---|
| Size | 7.15 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
219
40.9 IPS |
|
|
Image Classification (F16)
|
100% |
231
43.3 IPS |
|
|
Image Classification (I8)
|
97% |
462
86.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
304
5.07 IPS |
|
|
Image Segmentation (F16)
|
100% |
296
4.94 IPS |
|
|
Image Segmentation (I8)
|
98% |
366
6.12 IPS |
|
|
Pose Estimation (F32)
|
100% |
442
0.53 IPS |
|
|
Pose Estimation (F16)
|
100% |
457
0.55 IPS |
|
|
Pose Estimation (I8)
|
100% |
2076
2.51 IPS |
|
|
Object Detection (F32)
|
100% |
238
17.8 IPS |
|
|
Object Detection (F16)
|
100% |
246
18.4 IPS |
|
|
Object Detection (I8)
|
61% |
612
45.7 IPS |
|
|
Face Detection (F32)
|
100% |
461
5.49 IPS |
|
|
Face Detection (F16)
|
100% |
469
5.58 IPS |
|
|
Face Detection (I8)
|
86% |
1097
13.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
478
3.71 IPS |
|
|
Depth Estimation (F16)
|
100% |
477
3.70 IPS |
|
|
Depth Estimation (I8)
|
95% |
1094
8.48 IPS |
|
|
Style Transfer (F32)
|
100% |
773
1.02 IPS |
|
|
Style Transfer (F16)
|
100% |
618
0.81 IPS |
|
|
Style Transfer (I8)
|
98% |
1624
2.14 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
207
7.41 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
225
8.02 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
522
18.7 IPS |
|
|
Text Classification (F32)
|
100% |
142
204.4 IPS |
|
|
Text Classification (F16)
|
100% |
145
209.1 IPS |
|
|
Text Classification (I8)
|
92% |
128
183.7 IPS |
|
|
Machine Translation (F32)
|
100% |
420
7.74 IPS |
|
|
Machine Translation (F16)
|
100% |
427
7.86 IPS |
|
|
Machine Translation (I8)
|
64% |
148
2.73 IPS |
