OPPO CPH2557
Geekbench AI Score
518
Single Precision Score
515
Half Precision Score
947
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| User | likelake |
| Upload Date | November 07 2024 01:06 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM MT6833 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | OPPO CPH2557 |
| Model ID | OPPO CPH2557 |
| Motherboard | k6833v1_64_k419 |
| CPU Information | |
|---|---|
| Name | ARM MT6833 |
| 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 @ 2.20 GHz |
| Memory Information | |
|---|---|
| Size | 3.52 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
226
41.9 IPS |
|
|
Image Classification (HP)
|
100% |
227
42.2 IPS |
|
|
Image Classification (Q)
|
100% |
648
120.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
284
4.60 IPS |
|
|
Image Segmentation (HP)
|
100% |
282
4.58 IPS |
|
|
Image Segmentation (Q)
|
98% |
707
11.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
1112
1.30 IPS |
|
|
Pose Estimation (HP)
|
100% |
1102
1.29 IPS |
|
|
Pose Estimation (Q)
|
84% |
1640
1.95 IPS |
|
|
Object Detection (SP)
|
100% |
228
18.1 IPS |
|
|
Object Detection (HP)
|
100% |
228
18.1 IPS |
|
|
Object Detection (Q)
|
83% |
648
52.4 IPS |
|
|
Face Detection (SP)
|
100% |
726
8.62 IPS |
|
|
Face Detection (HP)
|
100% |
731
8.68 IPS |
|
|
Face Detection (Q)
|
95% |
1472
17.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
957
7.37 IPS |
|
|
Depth Estimation (HP)
|
99% |
945
7.28 IPS |
|
|
Depth Estimation (Q)
|
64% |
1498
13.7 IPS |
|
|
Style Transfer (SP)
|
89% |
1882
2.44 IPS |
|
|
Style Transfer (HP)
|
89% |
1882
2.44 IPS |
|
|
Style Transfer (Q)
|
98% |
3762
4.85 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
496
18.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
487
18.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
914
33.9 IPS |
|
|
Text Classification (SP)
|
100% |
278
371.2 IPS |
|
|
Text Classification (HP)
|
100% |
272
363.1 IPS |
|
|
Text Classification (Q)
|
88% |
461
621.4 IPS |
|
|
Machine Translation (SP)
|
100% |
476
8.20 IPS |
|
|
Machine Translation (HP)
|
100% |
478
8.23 IPS |
|
|
Machine Translation (Q)
|
50% |
341
12.1 IPS |
