OPPO CPH2761
Geekbench AI Score
1683
Single Precision Score
1597
Half Precision Score
2616
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | October 29 2025 04:32 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | OPPO CPH2761 |
| Model ID | OPPO CPH2761 |
| Motherboard | k6899v1_64 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3463 revision 1 |
| Base Frequency | 2.10 GHz |
| Cluster 1 | 4 Cores @ 2.10 GHz |
| Cluster 2 | 3 Cores @ 3.00 GHz |
| Cluster 3 | 1 Core @ 3.25 GHz |
| Memory Information | |
|---|---|
| Size | 7.29 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
903
167.9 IPS |
|
|
Image Classification (HP)
|
100% |
930
173.0 IPS |
|
|
Image Classification (Q)
|
100% |
1818
338.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
1314
21.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
1433
23.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
2240
36.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
2859
3.34 IPS |
|
|
Pose Estimation (HP)
|
100% |
2920
3.41 IPS |
|
|
Pose Estimation (Q)
|
84% |
6046
7.17 IPS |
|
|
Object Detection (SP)
|
98% |
1322
105.2 IPS |
|
|
Object Detection (HP)
|
98% |
856
68.1 IPS |
|
|
Object Detection (Q)
|
83% |
1799
145.4 IPS |
|
|
Face Detection (SP)
|
100% |
2803
33.3 IPS |
|
|
Face Detection (HP)
|
100% |
2845
33.8 IPS |
|
|
Face Detection (Q)
|
95% |
4225
50.4 IPS |
|
|
Depth Estimation (SP)
|
99% |
2977
23.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
2895
22.4 IPS |
|
|
Depth Estimation (Q)
|
64% |
4577
41.9 IPS |
|
|
Style Transfer (SP)
|
89% |
7172
9.31 IPS |
|
|
Style Transfer (HP)
|
89% |
6470
8.40 IPS |
|
|
Style Transfer (Q)
|
98% |
12381
16.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1321
48.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1108
40.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3173
117.6 IPS |
|
|
Text Classification (SP)
|
100% |
461
615.3 IPS |
|
|
Text Classification (HP)
|
99% |
489
652.3 IPS |
|
|
Text Classification (Q)
|
88% |
902
1.22 KIPS |
|
|
Machine Translation (SP)
|
100% |
1121
19.3 IPS |
|
|
Machine Translation (HP)
|
100% |
1123
19.3 IPS |
|
|
Machine Translation (Q)
|
50% |
496
17.6 IPS |
