oplus SM-S928B
Geekbench AI Score
458
Single Precision Score
466
Half Precision Score
1102
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | December 13 2024 06:36 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | oplus SM-S928B |
| Model ID | oplus SM-S928B |
| Motherboard | taro |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 2 part 3400 revision 0 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.50 GHz |
| Cluster 3 | 1 Core @ 3.00 GHz |
| Memory Information | |
|---|---|
| Size | 7.06 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
208
38.7 IPS |
|
|
Image Classification (HP)
|
100% |
212
39.4 IPS |
|
|
Image Classification (Q)
|
100% |
780
145.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
249
4.03 IPS |
|
|
Image Segmentation (HP)
|
100% |
248
4.01 IPS |
|
|
Image Segmentation (Q)
|
98% |
765
12.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
1019
1.19 IPS |
|
|
Pose Estimation (HP)
|
100% |
1002
1.17 IPS |
|
|
Pose Estimation (Q)
|
84% |
2298
2.72 IPS |
|
|
Object Detection (SP)
|
100% |
210
16.7 IPS |
|
|
Object Detection (HP)
|
100% |
210
16.6 IPS |
|
|
Object Detection (Q)
|
83% |
774
62.6 IPS |
|
|
Face Detection (SP)
|
100% |
622
7.39 IPS |
|
|
Face Detection (HP)
|
100% |
619
7.35 IPS |
|
|
Face Detection (Q)
|
95% |
1563
18.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
833
6.42 IPS |
|
|
Depth Estimation (HP)
|
99% |
847
6.52 IPS |
|
|
Depth Estimation (Q)
|
64% |
1743
16.0 IPS |
|
|
Style Transfer (SP)
|
89% |
1447
1.88 IPS |
|
|
Style Transfer (HP)
|
89% |
1651
2.14 IPS |
|
|
Style Transfer (Q)
|
98% |
4791
6.18 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
514
19.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
507
18.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1101
40.8 IPS |
|
|
Text Classification (SP)
|
100% |
229
306.2 IPS |
|
|
Text Classification (HP)
|
100% |
228
304.7 IPS |
|
|
Text Classification (Q)
|
88% |
486
655.8 IPS |
|
|
Machine Translation (SP)
|
100% |
424
7.31 IPS |
|
|
Machine Translation (HP)
|
100% |
439
7.55 IPS |
|
|
Machine Translation (Q)
|
50% |
359
12.7 IPS |
