OPPO CPH2659
Geekbench AI Score
1662
Single Precision Score
1623
Half Precision Score
1960
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| Upload Date | November 21 2024 04:36 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | OPPO CPH2659 |
| Model ID | OPPO CPH2659 |
| Motherboard | k6991v1_64 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3461 revision 1 |
| Base Frequency | 2.40 GHz |
| Cluster 1 | 4 Cores @ 2.40 GHz |
| Cluster 2 | 3 Cores @ 3.30 GHz |
| Cluster 3 | 1 Core @ 3.63 GHz |
| Memory Information | |
|---|---|
| Size | 15.03 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1226
228.1 IPS |
|
|
Image Classification (HP)
|
100% |
1201
223.4 IPS |
|
|
Image Classification (Q)
|
100% |
1724
320.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
1459
23.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
1529
24.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
2018
32.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
2715
3.17 IPS |
|
|
Pose Estimation (HP)
|
100% |
2377
2.77 IPS |
|
|
Pose Estimation (Q)
|
84% |
4407
5.23 IPS |
|
|
Object Detection (SP)
|
98% |
925
73.6 IPS |
|
|
Object Detection (HP)
|
98% |
931
74.1 IPS |
|
|
Object Detection (Q)
|
83% |
1302
105.2 IPS |
|
|
Face Detection (SP)
|
100% |
2229
26.5 IPS |
|
|
Face Detection (HP)
|
100% |
2292
27.2 IPS |
|
|
Face Detection (Q)
|
95% |
3223
38.5 IPS |
|
|
Depth Estimation (SP)
|
99% |
2832
21.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
2814
21.7 IPS |
|
|
Depth Estimation (Q)
|
64% |
3420
31.3 IPS |
|
|
Style Transfer (SP)
|
89% |
5525
7.17 IPS |
|
|
Style Transfer (HP)
|
89% |
5546
7.20 IPS |
|
|
Style Transfer (Q)
|
98% |
9733
12.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1235
45.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1205
44.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2090
77.5 IPS |
|
|
Text Classification (SP)
|
100% |
541
722.7 IPS |
|
|
Text Classification (HP)
|
99% |
530
707.9 IPS |
|
|
Text Classification (Q)
|
88% |
544
733.7 IPS |
|
|
Machine Translation (SP)
|
100% |
1541
26.5 IPS |
|
|
Machine Translation (HP)
|
100% |
1372
23.6 IPS |
|
|
Machine Translation (Q)
|
50% |
344
12.2 IPS |
