OPPO CPH2729
Geekbench AI Score
997
Single Precision Score
1013
Half Precision Score
1764
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | December 02 2025 05:04 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | OPPO CPH2729 |
| Model ID | OPPO CPH2729 |
| Motherboard | volcano |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3457 revision 1 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.21 GHz |
| Cluster 3 | 1 Core @ 2.30 GHz |
| Memory Information | |
|---|---|
| Size | 7.17 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
592
110.2 IPS |
|
|
Image Classification (HP)
|
100% |
837
155.7 IPS |
|
|
Image Classification (Q)
|
100% |
813
151.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
764
12.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
498
8.07 IPS |
|
|
Image Segmentation (Q)
|
98% |
1075
17.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
1864
2.17 IPS |
|
|
Pose Estimation (HP)
|
100% |
1923
2.24 IPS |
|
|
Pose Estimation (Q)
|
84% |
5217
6.19 IPS |
|
|
Object Detection (SP)
|
98% |
848
67.5 IPS |
|
|
Object Detection (HP)
|
98% |
648
51.6 IPS |
|
|
Object Detection (Q)
|
83% |
1636
132.2 IPS |
|
|
Face Detection (SP)
|
100% |
1177
14.0 IPS |
|
|
Face Detection (HP)
|
100% |
1054
12.5 IPS |
|
|
Face Detection (Q)
|
95% |
2810
33.5 IPS |
|
|
Depth Estimation (SP)
|
99% |
1563
12.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
1581
12.2 IPS |
|
|
Depth Estimation (Q)
|
64% |
2009
18.4 IPS |
|
|
Style Transfer (SP)
|
89% |
4340
5.63 IPS |
|
|
Style Transfer (HP)
|
89% |
4004
5.20 IPS |
|
|
Style Transfer (Q)
|
98% |
11456
14.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
705
26.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
684
25.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1214
45.0 IPS |
|
|
Text Classification (SP)
|
100% |
274
366.2 IPS |
|
|
Text Classification (HP)
|
99% |
538
718.6 IPS |
|
|
Text Classification (Q)
|
88% |
983
1.33 KIPS |
|
|
Machine Translation (SP)
|
100% |
883
15.2 IPS |
|
|
Machine Translation (HP)
|
100% |
898
15.5 IPS |
|
|
Machine Translation (Q)
|
50% |
509
18.1 IPS |
