OPPO PGEM10
Geekbench AI Score
1585
Single Precision Score
1571
Half Precision Score
2475
Quantized Score
Geekbench AI 1.0.0 for Android AArch64
Result Information
| User | 5j3rul3 |
| Upload Date | August 31 2024 01:48 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | OPPO PGEM10 |
| Model ID | OPPO PGEM10 |
| Motherboard | kalama |
| Governor | uag |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3406 revision 0 |
| Base Frequency | 2.02 GHz |
| Cluster 1 | 3 Cores @ 2.02 GHz |
| Cluster 2 | 4 Cores @ 2.80 GHz |
| Cluster 3 | 1 Core @ 3.19 GHz |
| Memory Information | |
|---|---|
| Size | 14.83 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1136
211.3 IPS |
|
|
Image Classification (HP)
|
100% |
895
166.4 IPS |
|
|
Image Classification (Q)
|
100% |
1747
324.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
1310
21.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
1232
20.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
1642
26.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
2249
2.62 IPS |
|
|
Pose Estimation (HP)
|
100% |
2289
2.67 IPS |
|
|
Pose Estimation (Q)
|
84% |
5150
6.11 IPS |
|
|
Object Detection (SP)
|
98% |
1225
97.5 IPS |
|
|
Object Detection (HP)
|
98% |
1277
101.6 IPS |
|
|
Object Detection (Q)
|
87% |
1825
146.6 IPS |
|
|
Face Detection (SP)
|
100% |
2440
29.0 IPS |
|
|
Face Detection (HP)
|
100% |
2404
28.6 IPS |
|
|
Face Detection (Q)
|
95% |
3783
45.2 IPS |
|
|
Depth Estimation (SP)
|
98% |
2390
18.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
2373
18.3 IPS |
|
|
Depth Estimation (Q)
|
75% |
4669
37.9 IPS |
|
|
Style Transfer (SP)
|
89% |
5953
7.73 IPS |
|
|
Style Transfer (HP)
|
89% |
5970
7.75 IPS |
|
|
Style Transfer (Q)
|
98% |
11107
14.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1109
40.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1281
47.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2782
103.1 IPS |
|
|
Text Classification (SP)
|
100% |
477
636.2 IPS |
|
|
Text Classification (HP)
|
99% |
514
686.5 IPS |
|
|
Text Classification (Q)
|
88% |
918
1.24 KIPS |
|
|
Machine Translation (SP)
|
100% |
1331
22.9 IPS |
|
|
Machine Translation (HP)
|
100% |
1274
21.9 IPS |
|
|
Machine Translation (Q)
|
50% |
641
22.8 IPS |
