OPPO OPD2402
Geekbench AI Score
2522
Single Precision Score
2508
Half Precision Score
2984
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | January 08 2025 03:07 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | OPPO OPD2402 |
| Model ID | OPPO OPD2402 |
| Motherboard | pineapple |
| Governor | uag |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.26 GHz |
| Cluster 1 | 2 Cores @ 2.27 GHz |
| Cluster 2 | 2 Cores @ 2.96 GHz |
| Cluster 3 | 3 Cores @ 3.15 GHz |
| Cluster 4 | 1 Core @ 3.40 GHz |
| Memory Information | |
|---|---|
| Size | 11.30 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1669
310.4 IPS |
|
|
Image Classification (HP)
|
100% |
1704
316.8 IPS |
|
|
Image Classification (Q)
|
100% |
2568
477.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
2422
39.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
2354
38.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
3220
52.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
4257
4.97 IPS |
|
|
Pose Estimation (HP)
|
100% |
3834
4.47 IPS |
|
|
Pose Estimation (Q)
|
84% |
8097
9.60 IPS |
|
|
Object Detection (SP)
|
98% |
1628
129.5 IPS |
|
|
Object Detection (HP)
|
98% |
1628
129.5 IPS |
|
|
Object Detection (Q)
|
83% |
2063
166.7 IPS |
|
|
Face Detection (SP)
|
100% |
3550
42.2 IPS |
|
|
Face Detection (HP)
|
100% |
3562
42.3 IPS |
|
|
Face Detection (Q)
|
95% |
5475
65.4 IPS |
|
|
Depth Estimation (SP)
|
99% |
3955
30.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
3858
29.8 IPS |
|
|
Depth Estimation (Q)
|
64% |
5061
46.4 IPS |
|
|
Style Transfer (SP)
|
89% |
9225
12.0 IPS |
|
|
Style Transfer (HP)
|
89% |
9502
12.3 IPS |
|
|
Style Transfer (Q)
|
98% |
16197
20.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1648
60.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1729
63.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3058
113.3 IPS |
|
|
Text Classification (SP)
|
100% |
973
1.30 KIPS |
|
|
Text Classification (HP)
|
99% |
1015
1.36 KIPS |
|
|
Text Classification (Q)
|
88% |
774
1.04 KIPS |
|
|
Machine Translation (SP)
|
100% |
1796
30.9 IPS |
|
|
Machine Translation (HP)
|
100% |
1722
29.7 IPS |
|
|
Machine Translation (Q)
|
50% |
382
13.6 IPS |
