OPPO CPH2669
Geekbench AI Score
28
Single Precision Score
84
Half Precision Score
83
Quantized Score
Geekbench AI 1.0.0 for Android AArch64
Result Information
| Upload Date | August 21 2024 09:35 PM |
| Views | 19 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Qualcomm ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | OPPO CPH2669 |
| Model ID | OPPO CPH2669 |
| Motherboard | bengal |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | Qualcomm ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 10 part 2048 revision 2 |
| Base Frequency | 2.02 GHz |
| Cluster 1 | 4 Cores @ 2.02 GHz |
| Cluster 2 | 4 Cores @ 2.11 GHz |
| Memory Information | |
|---|---|
| Size | 5.45 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
30
5.58 IPS |
|
|
Image Classification (HP)
|
100% |
59
11.0 IPS |
|
|
Image Classification (Q)
|
97% |
60
11.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
29
0.47 IPS |
|
|
Image Segmentation (HP)
|
100% |
90
1.46 IPS |
|
|
Image Segmentation (Q)
|
98% |
84
1.36 IPS |
|
|
Pose Estimation (SP)
|
100% |
52
0.06 IPS |
|
|
Pose Estimation (HP)
|
100% |
99
0.12 IPS |
|
|
Pose Estimation (Q)
|
95% |
99
0.12 IPS |
|
|
Object Detection (SP)
|
100% |
29
2.32 IPS |
|
|
Object Detection (HP)
|
100% |
48
3.84 IPS |
|
|
Object Detection (Q)
|
86% |
47
3.81 IPS |
|
|
Face Detection (SP)
|
100% |
75
0.89 IPS |
|
|
Face Detection (HP)
|
100% |
185
2.20 IPS |
|
|
Face Detection (Q)
|
97% |
191
2.28 IPS |
|
|
Depth Estimation (SP)
|
100% |
69
0.53 IPS |
|
|
Depth Estimation (HP)
|
99% |
141
1.09 IPS |
|
|
Depth Estimation (Q)
|
75% |
133
1.08 IPS |
|
|
Style Transfer (SP)
|
0
|
||
|
Style Transfer (HP)
|
100% |
258
0.33 IPS |
|
|
Style Transfer (Q)
|
98% |
258
0.33 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
34
1.25 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
69
2.55 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
69
2.55 IPS |
|
|
Text Classification (SP)
|
100% |
27
35.8 IPS |
|
|
Text Classification (HP)
|
100% |
27
36.0 IPS |
|
|
Text Classification (Q)
|
91% |
36
47.9 IPS |
|
|
Machine Translation (SP)
|
100% |
59
1.02 IPS |
|
|
Machine Translation (HP)
|
100% |
59
1.01 IPS |
|
|
Machine Translation (Q)
|
57% |
44
1.07 IPS |
