OPPO CPH2337
Geekbench AI Score
306
Single Precision Score
521
Half Precision Score
449
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| Upload Date | January 14 2026 04:32 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM MT6833V/PNZA |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | OPPO CPH2337 |
| Model ID | OPPO CPH2337 |
| Motherboard | k6833v1_64_k419 |
| CPU Information | |
|---|---|
| Name | ARM MT6833V/PNZA |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 4 part 3339 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 6 Cores @ 2.00 GHz |
| Cluster 2 | 2 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 7.45 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
188
35.0 IPS |
|
|
Image Classification (HP)
|
100% |
278
51.7 IPS |
|
|
Image Classification (Q)
|
97% |
251
46.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
275
4.46 IPS |
|
|
Image Segmentation (HP)
|
100% |
592
9.60 IPS |
|
|
Image Segmentation (Q)
|
98% |
554
9.00 IPS |
|
|
Pose Estimation (SP)
|
100% |
1228
1.43 IPS |
|
|
Pose Estimation (HP)
|
100% |
2198
2.56 IPS |
|
|
Pose Estimation (Q)
|
95% |
2177
2.55 IPS |
|
|
Object Detection (SP)
|
100% |
172
13.6 IPS |
|
|
Object Detection (HP)
|
99% |
352
27.9 IPS |
|
|
Object Detection (Q)
|
83% |
389
31.4 IPS |
|
|
Face Detection (SP)
|
100% |
650
7.73 IPS |
|
|
Face Detection (HP)
|
100% |
1251
14.9 IPS |
|
|
Face Detection (Q)
|
96% |
1114
13.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
876
6.75 IPS |
|
|
Depth Estimation (HP)
|
98% |
1640
12.7 IPS |
|
|
Depth Estimation (Q)
|
62% |
1327
12.6 IPS |
|
|
Style Transfer (SP)
|
100% |
2262
2.91 IPS |
|
|
Style Transfer (HP)
|
100% |
4422
5.68 IPS |
|
|
Style Transfer (Q)
|
98% |
4306
5.55 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
498
18.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
675
24.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
675
25.0 IPS |
|
|
Text Classification (SP)
|
29% |
5
80.7 IPS |
|
|
Text Classification (HP)
|
29% |
7
117.9 IPS |
|
|
Text Classification (Q)
|
32% |
10
129.4 IPS |
|
|
Machine Translation (SP)
|
100% |
208
3.58 IPS |
|
|
Machine Translation (HP)
|
100% |
273
4.70 IPS |
|
|
Machine Translation (Q)
|
43% |
66
3.86 IPS |
