OPPO CPH2743
Geekbench AI Score
762
Single Precision Score
825
Half Precision Score
1472
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | batu69 |
| Upload Date | September 09 2025 04:22 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | OPPO CPH2743 |
| Model ID | OPPO CPH2743 |
| Motherboard | parrot |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 2 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 4 Cores @ 2.21 GHz |
| Memory Information | |
|---|---|
| Size | 7.25 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
194
36.1 IPS |
|
|
Image Classification (HP)
|
100% |
428
79.6 IPS |
|
|
Image Classification (Q)
|
100% |
1334
248.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
510
8.27 IPS |
|
|
Image Segmentation (HP)
|
100% |
519
8.41 IPS |
|
|
Image Segmentation (Q)
|
98% |
1552
25.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
1921
2.24 IPS |
|
|
Pose Estimation (HP)
|
100% |
1885
2.20 IPS |
|
|
Pose Estimation (Q)
|
84% |
3383
4.01 IPS |
|
|
Object Detection (SP)
|
100% |
425
33.7 IPS |
|
|
Object Detection (HP)
|
100% |
431
34.1 IPS |
|
|
Object Detection (Q)
|
83% |
1299
104.9 IPS |
|
|
Face Detection (SP)
|
100% |
1099
13.1 IPS |
|
|
Face Detection (HP)
|
100% |
1100
13.1 IPS |
|
|
Face Detection (Q)
|
95% |
3191
38.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
739
5.69 IPS |
|
|
Depth Estimation (HP)
|
99% |
752
5.79 IPS |
|
|
Depth Estimation (Q)
|
64% |
3172
29.1 IPS |
|
|
Style Transfer (SP)
|
89% |
3488
4.53 IPS |
|
|
Style Transfer (HP)
|
89% |
3485
4.52 IPS |
|
|
Style Transfer (Q)
|
98% |
7970
10.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
848
31.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
853
31.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1905
70.6 IPS |
|
|
Text Classification (SP)
|
100% |
479
638.9 IPS |
|
|
Text Classification (HP)
|
100% |
467
623.6 IPS |
|
|
Text Classification (Q)
|
88% |
881
1.19 KIPS |
|
|
Machine Translation (SP)
|
100% |
713
12.3 IPS |
|
|
Machine Translation (HP)
|
100% |
708
12.2 IPS |
|
|
Machine Translation (Q)
|
50% |
39
1.37 IPS |
