OPPO CPH2477
Geekbench AI Score
239
Single Precision Score
243
Half Precision Score
261
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 19 2025 04:26 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM MT6765G |
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | OPPO CPH2477 |
| Model ID | OPPO CPH2477 |
| Motherboard | k65v1_64_bsp |
| CPU Information | |
|---|---|
| Name | ARM MT6765G |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3331 revision 4 |
| Base Frequency | 2.30 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 4 Cores @ 2.30 GHz |
| Memory Information | |
|---|---|
| Size | 3.71 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
84
15.6 IPS |
|
|
Image Classification (HP)
|
100% |
103
19.1 IPS |
|
|
Image Classification (Q)
|
100% |
173
32.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
160
2.59 IPS |
|
|
Image Segmentation (HP)
|
100% |
157
2.54 IPS |
|
|
Image Segmentation (Q)
|
98% |
271
4.40 IPS |
|
|
Pose Estimation (SP)
|
100% |
635
0.74 IPS |
|
|
Pose Estimation (HP)
|
100% |
605
0.71 IPS |
|
|
Pose Estimation (Q)
|
84% |
435
0.52 IPS |
|
|
Object Detection (SP)
|
100% |
132
10.5 IPS |
|
|
Object Detection (HP)
|
100% |
132
10.5 IPS |
|
|
Object Detection (Q)
|
83% |
165
13.3 IPS |
|
|
Face Detection (SP)
|
100% |
343
4.08 IPS |
|
|
Face Detection (HP)
|
100% |
333
3.96 IPS |
|
|
Face Detection (Q)
|
95% |
500
5.97 IPS |
|
|
Depth Estimation (SP)
|
100% |
423
3.26 IPS |
|
|
Depth Estimation (HP)
|
99% |
387
2.98 IPS |
|
|
Depth Estimation (Q)
|
64% |
407
3.73 IPS |
|
|
Style Transfer (SP)
|
89% |
1148
1.49 IPS |
|
|
Style Transfer (HP)
|
89% |
1201
1.56 IPS |
|
|
Style Transfer (Q)
|
98% |
1155
1.49 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
191
7.06 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
187
6.91 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
232
8.58 IPS |
|
|
Text Classification (SP)
|
100% |
92
123.0 IPS |
|
|
Text Classification (HP)
|
100% |
119
158.2 IPS |
|
|
Text Classification (Q)
|
88% |
113
152.3 IPS |
|
|
Machine Translation (SP)
|
100% |
185
3.18 IPS |
|
|
Machine Translation (HP)
|
100% |
162
2.79 IPS |
|
|
Machine Translation (Q)
|
50% |
71
2.50 IPS |
