OPPO OPD2409
Geekbench AI Score
2380
Single Precision Score
2428
Half Precision Score
4491
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| Upload Date | February 06 2026 02:56 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | OPPO OPD2409 |
| Model ID | OPPO OPD2409 |
| Motherboard | sun |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | Qualcomm ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 3 part 1 revision 4 |
| Base Frequency | 3.53 GHz |
| Cluster 1 | 6 Cores @ 3.53 GHz |
| Cluster 2 | 2 Cores @ 4.32 GHz |
| Memory Information | |
|---|---|
| Size | 15.07 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1329
247.1 IPS |
|
|
Image Classification (HP)
|
100% |
1604
298.3 IPS |
|
|
Image Classification (Q)
|
100% |
3071
571.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
1825
29.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
1706
27.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
4320
70.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
4147
4.84 IPS |
|
|
Pose Estimation (HP)
|
100% |
4342
5.07 IPS |
|
|
Pose Estimation (Q)
|
84% |
10751
12.8 IPS |
|
|
Object Detection (SP)
|
98% |
1387
110.4 IPS |
|
|
Object Detection (HP)
|
98% |
1361
108.3 IPS |
|
|
Object Detection (Q)
|
83% |
3496
282.4 IPS |
|
|
Face Detection (SP)
|
100% |
3835
45.6 IPS |
|
|
Face Detection (HP)
|
100% |
4063
48.3 IPS |
|
|
Face Detection (Q)
|
95% |
9687
115.6 IPS |
|
|
Depth Estimation (SP)
|
99% |
4004
30.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
4079
31.5 IPS |
|
|
Depth Estimation (Q)
|
64% |
9055
82.9 IPS |
|
|
Style Transfer (SP)
|
89% |
10261
13.3 IPS |
|
|
Style Transfer (HP)
|
89% |
10218
13.3 IPS |
|
|
Style Transfer (Q)
|
98% |
23040
29.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2105
77.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2030
75.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
6437
238.5 IPS |
|
|
Text Classification (SP)
|
100% |
959
1.28 KIPS |
|
|
Text Classification (HP)
|
99% |
966
1.29 KIPS |
|
|
Text Classification (Q)
|
88% |
1022
1.38 KIPS |
|
|
Machine Translation (SP)
|
100% |
1319
22.7 IPS |
|
|
Machine Translation (HP)
|
100% |
1326
22.8 IPS |
|
|
Machine Translation (Q)
|
50% |
504
17.9 IPS |
