OPPO CPH2761
Geekbench AI Score
1541
Single Precision Score
1609
Half Precision Score
2374
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | October 29 2025 04:47 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% |
650
120.8 IPS |
|
|
Image Classification (HP)
|
100% |
1050
195.3 IPS |
|
|
Image Classification (Q)
|
100% |
1684
313.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
1394
22.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
1345
21.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
1995
32.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
2467
2.88 IPS |
|
|
Pose Estimation (HP)
|
100% |
2475
2.89 IPS |
|
|
Pose Estimation (Q)
|
84% |
5426
6.44 IPS |
|
|
Object Detection (SP)
|
98% |
1220
97.1 IPS |
|
|
Object Detection (HP)
|
98% |
1260
100.2 IPS |
|
|
Object Detection (Q)
|
83% |
1622
131.0 IPS |
|
|
Face Detection (SP)
|
100% |
2619
31.1 IPS |
|
|
Face Detection (HP)
|
100% |
2602
30.9 IPS |
|
|
Face Detection (Q)
|
95% |
3932
46.9 IPS |
|
|
Depth Estimation (SP)
|
99% |
2659
20.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
2472
19.1 IPS |
|
|
Depth Estimation (Q)
|
64% |
3912
35.8 IPS |
|
|
Style Transfer (SP)
|
89% |
6249
8.11 IPS |
|
|
Style Transfer (HP)
|
89% |
6143
7.97 IPS |
|
|
Style Transfer (Q)
|
98% |
11629
15.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1166
43.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1194
44.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2854
105.8 IPS |
|
|
Text Classification (SP)
|
100% |
512
683.4 IPS |
|
|
Text Classification (HP)
|
99% |
539
718.9 IPS |
|
|
Text Classification (Q)
|
88% |
822
1.11 KIPS |
|
|
Machine Translation (SP)
|
100% |
1071
18.5 IPS |
|
|
Machine Translation (HP)
|
100% |
1043
18.0 IPS |
|
|
Machine Translation (Q)
|
50% |
459
16.3 IPS |
