samsung SM-S928U1
Geekbench ML Score
694
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 17 2024 09:12 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-S928U1 |
| Model ID | samsung SM-S928U1 |
| Motherboard | pineapple |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.26 GHz |
| Cluster 1 | 2 Cores @ 2.27 GHz |
| Cluster 2 | 2 Cores @ 2.96 GHz |
| Cluster 3 | 3 Cores @ 3.15 GHz |
| Cluster 4 | 1 Core @ 3.40 GHz |
| Memory Information | |
|---|---|
| Size | 10.81 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
315
58.9 IPS |
|
|
Image Classification (F16)
|
100% |
311
58.1 IPS |
|
|
Image Classification (I8)
|
97% |
817
153.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
388
6.49 IPS |
|
|
Image Segmentation (F16)
|
100% |
383
6.39 IPS |
|
|
Image Segmentation (I8)
|
98% |
798
13.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
544
0.66 IPS |
|
|
Pose Estimation (F16)
|
100% |
537
0.65 IPS |
|
|
Pose Estimation (I8)
|
100% |
2046
2.48 IPS |
|
|
Object Detection (F32)
|
100% |
321
24.0 IPS |
|
|
Object Detection (F16)
|
100% |
324
24.2 IPS |
|
|
Object Detection (I8)
|
61% |
878
65.6 IPS |
|
|
Face Detection (F32)
|
100% |
764
9.08 IPS |
|
|
Face Detection (F16)
|
100% |
762
9.05 IPS |
|
|
Face Detection (I8)
|
86% |
1807
21.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
692
5.37 IPS |
|
|
Depth Estimation (F16)
|
100% |
687
5.33 IPS |
|
|
Depth Estimation (I8)
|
95% |
1898
14.7 IPS |
|
|
Style Transfer (F32)
|
100% |
1069
1.41 IPS |
|
|
Style Transfer (F16)
|
100% |
1064
1.40 IPS |
|
|
Style Transfer (I8)
|
98% |
2641
3.47 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
375
13.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
379
13.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1283
45.8 IPS |
|
|
Text Classification (F32)
|
100% |
443
636.6 IPS |
|
|
Text Classification (F16)
|
100% |
445
640.2 IPS |
|
|
Text Classification (I8)
|
92% |
734
1.05 KIPS |
|
|
Machine Translation (F32)
|
100% |
739
13.6 IPS |
|
|
Machine Translation (F16)
|
100% |
731
13.5 IPS |
|
|
Machine Translation (I8)
|
64% |
849
15.6 IPS |
