OPPO CPH2739
Geekbench AI Score
1811
Single Precision Score
1807
Half Precision Score
2692
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | October 22 2025 08:24 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | OPPO CPH2739 |
| Model ID | OPPO CPH2739 |
| 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 | 11.19 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1334
248.2 IPS |
|
|
Image Classification (HP)
|
100% |
1434
266.6 IPS |
|
|
Image Classification (Q)
|
100% |
2146
399.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
1599
25.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
1633
26.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
2478
40.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
2910
3.40 IPS |
|
|
Pose Estimation (HP)
|
100% |
2905
3.39 IPS |
|
|
Pose Estimation (Q)
|
84% |
7008
8.31 IPS |
|
|
Object Detection (SP)
|
98% |
1309
104.2 IPS |
|
|
Object Detection (HP)
|
98% |
1341
106.7 IPS |
|
|
Object Detection (Q)
|
83% |
1774
143.3 IPS |
|
|
Face Detection (SP)
|
100% |
2860
34.0 IPS |
|
|
Face Detection (HP)
|
100% |
2762
32.8 IPS |
|
|
Face Detection (Q)
|
95% |
4175
49.8 IPS |
|
|
Depth Estimation (SP)
|
99% |
2982
23.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
2940
22.7 IPS |
|
|
Depth Estimation (Q)
|
64% |
4656
42.6 IPS |
|
|
Style Transfer (SP)
|
89% |
6998
9.08 IPS |
|
|
Style Transfer (HP)
|
89% |
6565
8.52 IPS |
|
|
Style Transfer (Q)
|
98% |
12755
16.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1240
45.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1250
46.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3173
117.6 IPS |
|
|
Text Classification (SP)
|
100% |
570
760.9 IPS |
|
|
Text Classification (HP)
|
99% |
532
710.5 IPS |
|
|
Text Classification (Q)
|
88% |
826
1.11 KIPS |
|
|
Machine Translation (SP)
|
100% |
1108
19.1 IPS |
|
|
Machine Translation (HP)
|
100% |
1152
19.8 IPS |
|
|
Machine Translation (Q)
|
50% |
466
16.5 IPS |
