OPPO CPH2337
Geekbench AI Score
478
Single Precision Score
476
Half Precision Score
866
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| Upload Date | January 14 2026 04:24 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
223
41.6 IPS |
|
|
Image Classification (HP)
|
100% |
222
41.3 IPS |
|
|
Image Classification (Q)
|
100% |
627
116.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
276
4.48 IPS |
|
|
Image Segmentation (HP)
|
100% |
277
4.48 IPS |
|
|
Image Segmentation (Q)
|
98% |
700
11.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
1020
1.19 IPS |
|
|
Pose Estimation (HP)
|
100% |
1010
1.18 IPS |
|
|
Pose Estimation (Q)
|
84% |
1453
1.72 IPS |
|
|
Object Detection (SP)
|
100% |
205
16.3 IPS |
|
|
Object Detection (HP)
|
100% |
204
16.2 IPS |
|
|
Object Detection (Q)
|
83% |
580
46.8 IPS |
|
|
Face Detection (SP)
|
100% |
677
8.05 IPS |
|
|
Face Detection (HP)
|
100% |
674
8.01 IPS |
|
|
Face Detection (Q)
|
95% |
1314
15.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
866
6.67 IPS |
|
|
Depth Estimation (HP)
|
99% |
857
6.60 IPS |
|
|
Depth Estimation (Q)
|
64% |
1337
12.2 IPS |
|
|
Style Transfer (SP)
|
89% |
1697
2.20 IPS |
|
|
Style Transfer (HP)
|
89% |
1703
2.21 IPS |
|
|
Style Transfer (Q)
|
98% |
3334
4.30 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
461
17.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
459
16.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
803
29.8 IPS |
|
|
Text Classification (SP)
|
100% |
247
329.1 IPS |
|
|
Text Classification (HP)
|
100% |
246
328.7 IPS |
|
|
Text Classification (Q)
|
88% |
440
593.2 IPS |
|
|
Machine Translation (SP)
|
100% |
431
7.42 IPS |
|
|
Machine Translation (HP)
|
100% |
430
7.40 IPS |
|
|
Machine Translation (Q)
|
50% |
313
11.1 IPS |
