OPPO CPH2737
Geekbench AI Score
1838
Single Precision Score
1810
Half Precision Score
3234
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | July 03 2025 04:28 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | OPPO CPH2737 |
| Model ID | OPPO CPH2737 |
| Motherboard | k6897v1_64 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3405 revision 0 |
| Base Frequency | 2.20 GHz |
| Cluster 1 | 4 Cores @ 2.20 GHz |
| Cluster 2 | 3 Cores @ 3.20 GHz |
| Cluster 3 | 1 Core @ 3.35 GHz |
| Memory Information | |
|---|---|
| Size | 11.21 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1411
262.4 IPS |
|
|
Image Classification (HP)
|
100% |
1374
255.5 IPS |
|
|
Image Classification (Q)
|
100% |
2294
426.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
1487
24.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
1482
24.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
2628
42.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
2594
3.03 IPS |
|
|
Pose Estimation (HP)
|
100% |
2585
3.02 IPS |
|
|
Pose Estimation (Q)
|
84% |
6312
7.49 IPS |
|
|
Object Detection (SP)
|
98% |
1389
110.5 IPS |
|
|
Object Detection (HP)
|
98% |
1300
103.5 IPS |
|
|
Object Detection (Q)
|
83% |
2206
178.2 IPS |
|
|
Face Detection (SP)
|
100% |
2490
29.6 IPS |
|
|
Face Detection (HP)
|
100% |
2466
29.3 IPS |
|
|
Face Detection (Q)
|
95% |
5367
64.1 IPS |
|
|
Depth Estimation (SP)
|
99% |
2603
20.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
2495
19.3 IPS |
|
|
Depth Estimation (Q)
|
64% |
5339
48.9 IPS |
|
|
Style Transfer (SP)
|
89% |
6499
8.44 IPS |
|
|
Style Transfer (HP)
|
89% |
6604
8.57 IPS |
|
|
Style Transfer (Q)
|
98% |
13369
17.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1254
46.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1276
47.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3640
134.9 IPS |
|
|
Text Classification (SP)
|
100% |
748
998.4 IPS |
|
|
Text Classification (HP)
|
99% |
746
995.9 IPS |
|
|
Text Classification (Q)
|
88% |
1420
1.91 KIPS |
|
|
Machine Translation (SP)
|
100% |
1478
25.5 IPS |
|
|
Machine Translation (HP)
|
100% |
1428
24.6 IPS |
|
|
Machine Translation (Q)
|
50% |
753
26.7 IPS |
