OPPO CPH2483
Geekbench AI Score
241
Single Precision Score
248
Half Precision Score
269
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | August 29 2025 02:23 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM MT6762G |
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | OPPO CPH2483 |
| Model ID | OPPO CPH2483 |
| Motherboard | k65v1_64_bsp |
| CPU Information | |
|---|---|
| Name | ARM MT6762G |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3331 revision 4 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores @ 1.50 GHz |
| Cluster 2 | 4 Cores @ 2.00 GHz |
| Memory Information | |
|---|---|
| Size | 2.73 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
120
22.3 IPS |
|
|
Image Classification (HP)
|
100% |
119
22.2 IPS |
|
|
Image Classification (Q)
|
100% |
193
35.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
151
2.45 IPS |
|
|
Image Segmentation (HP)
|
100% |
159
2.58 IPS |
|
|
Image Segmentation (Q)
|
98% |
234
3.81 IPS |
|
|
Pose Estimation (SP)
|
100% |
532
0.62 IPS |
|
|
Pose Estimation (HP)
|
100% |
557
0.65 IPS |
|
|
Pose Estimation (Q)
|
84% |
417
0.49 IPS |
|
|
Object Detection (SP)
|
100% |
123
9.74 IPS |
|
|
Object Detection (HP)
|
100% |
125
9.95 IPS |
|
|
Object Detection (Q)
|
83% |
178
14.4 IPS |
|
|
Face Detection (SP)
|
100% |
332
3.94 IPS |
|
|
Face Detection (HP)
|
100% |
335
3.97 IPS |
|
|
Face Detection (Q)
|
95% |
517
6.18 IPS |
|
|
Depth Estimation (SP)
|
100% |
454
3.50 IPS |
|
|
Depth Estimation (HP)
|
99% |
401
3.09 IPS |
|
|
Depth Estimation (Q)
|
64% |
382
3.49 IPS |
|
|
Style Transfer (SP)
|
89% |
1061
1.38 IPS |
|
|
Style Transfer (HP)
|
89% |
1091
1.42 IPS |
|
|
Style Transfer (Q)
|
98% |
1054
1.36 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
160
5.91 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
199
7.34 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
247
9.15 IPS |
|
|
Text Classification (SP)
|
100% |
125
167.4 IPS |
|
|
Text Classification (HP)
|
100% |
129
171.9 IPS |
|
|
Text Classification (Q)
|
88% |
139
187.6 IPS |
|
|
Machine Translation (SP)
|
100% |
180
3.10 IPS |
|
|
Machine Translation (HP)
|
100% |
180
3.09 IPS |
|
|
Machine Translation (Q)
|
50% |
85
3.02 IPS |
