samsung SM-E156B
Geekbench AI Score
470
Single Precision Score
479
Half Precision Score
901
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | January 06 2025 11:29 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-E156B |
| Model ID | samsung SM-E156B |
| Motherboard | m15x |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| 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 | 3.50 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
207
38.6 IPS |
|
|
Image Classification (HP)
|
100% |
206
38.3 IPS |
|
|
Image Classification (Q)
|
100% |
620
115.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
257
4.17 IPS |
|
|
Image Segmentation (HP)
|
100% |
258
4.18 IPS |
|
|
Image Segmentation (Q)
|
98% |
683
11.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
1020
1.19 IPS |
|
|
Pose Estimation (HP)
|
100% |
1020
1.19 IPS |
|
|
Pose Estimation (Q)
|
84% |
1588
1.88 IPS |
|
|
Object Detection (SP)
|
100% |
212
16.8 IPS |
|
|
Object Detection (HP)
|
100% |
211
16.8 IPS |
|
|
Object Detection (Q)
|
83% |
593
47.9 IPS |
|
|
Face Detection (SP)
|
100% |
706
8.39 IPS |
|
|
Face Detection (HP)
|
100% |
698
8.29 IPS |
|
|
Face Detection (Q)
|
95% |
1422
17.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
737
5.68 IPS |
|
|
Depth Estimation (HP)
|
99% |
882
6.80 IPS |
|
|
Depth Estimation (Q)
|
64% |
1434
13.1 IPS |
|
|
Style Transfer (SP)
|
89% |
1750
2.27 IPS |
|
|
Style Transfer (HP)
|
89% |
1756
2.28 IPS |
|
|
Style Transfer (Q)
|
98% |
3566
4.60 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
457
16.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
471
17.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
855
31.7 IPS |
|
|
Text Classification (SP)
|
100% |
250
334.2 IPS |
|
|
Text Classification (HP)
|
100% |
246
328.9 IPS |
|
|
Text Classification (Q)
|
88% |
447
603.1 IPS |
|
|
Machine Translation (SP)
|
100% |
440
7.58 IPS |
|
|
Machine Translation (HP)
|
100% |
444
7.64 IPS |
|
|
Machine Translation (Q)
|
50% |
321
11.4 IPS |
