OPPO OPD2402
Geekbench AI Score
2558
Single Precision Score
2496
Half Precision Score
3011
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | January 08 2025 03:12 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% |
1982
368.7 IPS |
|
|
Image Classification (HP)
|
100% |
1687
313.8 IPS |
|
|
Image Classification (Q)
|
100% |
2604
484.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
2400
38.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
2353
38.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
3400
55.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
4236
4.94 IPS |
|
|
Pose Estimation (HP)
|
100% |
3820
4.46 IPS |
|
|
Pose Estimation (Q)
|
84% |
8011
9.50 IPS |
|
|
Object Detection (SP)
|
98% |
1656
131.8 IPS |
|
|
Object Detection (HP)
|
98% |
1619
128.8 IPS |
|
|
Object Detection (Q)
|
83% |
2104
170.0 IPS |
|
|
Face Detection (SP)
|
100% |
3633
43.2 IPS |
|
|
Face Detection (HP)
|
100% |
3626
43.1 IPS |
|
|
Face Detection (Q)
|
95% |
5278
63.0 IPS |
|
|
Depth Estimation (SP)
|
99% |
3880
30.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
3825
29.6 IPS |
|
|
Depth Estimation (Q)
|
64% |
4963
45.5 IPS |
|
|
Style Transfer (SP)
|
89% |
9696
12.6 IPS |
|
|
Style Transfer (HP)
|
89% |
9431
12.2 IPS |
|
|
Style Transfer (Q)
|
98% |
17095
22.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1738
64.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1719
63.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3179
117.8 IPS |
|
|
Text Classification (SP)
|
100% |
982
1.31 KIPS |
|
|
Text Classification (HP)
|
99% |
1004
1.34 KIPS |
|
|
Text Classification (Q)
|
88% |
761
1.03 KIPS |
|
|
Machine Translation (SP)
|
100% |
1544
26.6 IPS |
|
|
Machine Translation (HP)
|
100% |
1700
29.3 IPS |
|
|
Machine Translation (Q)
|
50% |
380
13.5 IPS |
