OPPO CPH2699
Geekbench AI Score
187
Single Precision Score
267
Half Precision Score
288
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | sebeg_the_tea_boii |
| Upload Date | March 28 2025 11:57 AM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | OPPO CPH2699 |
| Model ID | OPPO CPH2699 |
| Motherboard | parrot |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 2 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 4 Cores @ 2.21 GHz |
| Memory Information | |
|---|---|
| Size | 11.14 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
121
22.5 IPS |
|
|
Image Classification (HP)
|
100% |
215
40.0 IPS |
|
|
Image Classification (Q)
|
96% |
208
38.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
210
3.41 IPS |
|
|
Image Segmentation (HP)
|
100% |
288
4.67 IPS |
|
|
Image Segmentation (Q)
|
98% |
273
4.43 IPS |
|
|
Pose Estimation (SP)
|
100% |
175
0.20 IPS |
|
|
Pose Estimation (HP)
|
100% |
278
0.32 IPS |
|
|
Pose Estimation (Q)
|
96% |
277
0.32 IPS |
|
|
Object Detection (SP)
|
100% |
99
7.83 IPS |
|
|
Object Detection (HP)
|
100% |
152
12.0 IPS |
|
|
Object Detection (Q)
|
87% |
151
12.1 IPS |
|
|
Face Detection (SP)
|
100% |
367
4.36 IPS |
|
|
Face Detection (HP)
|
100% |
509
6.05 IPS |
|
|
Face Detection (Q)
|
97% |
484
5.78 IPS |
|
|
Depth Estimation (SP)
|
100% |
267
2.06 IPS |
|
|
Depth Estimation (HP)
|
99% |
440
3.40 IPS |
|
|
Depth Estimation (Q)
|
63% |
367
3.40 IPS |
|
|
Style Transfer (SP)
|
100% |
600
0.77 IPS |
|
|
Style Transfer (HP)
|
100% |
1204
1.55 IPS |
|
|
Style Transfer (Q)
|
98% |
1218
1.57 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
108
4.00 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
140
5.17 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
135
5.00 IPS |
|
|
Text Classification (SP)
|
100% |
104
139.4 IPS |
|
|
Text Classification (HP)
|
100% |
104
139.4 IPS |
|
|
Text Classification (Q)
|
91% |
253
339.6 IPS |
|
|
Machine Translation (SP)
|
100% |
182
3.14 IPS |
|
|
Machine Translation (HP)
|
100% |
182
3.14 IPS |
|
|
Machine Translation (Q)
|
57% |
224
5.49 IPS |
