samsung SM-S928W
Geekbench ML Score
1300
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| User | SyderAkaris |
| Upload Date | July 13 2024 04:08 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-S928W |
| Model ID | samsung SM-S928W |
| 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
590
110.4 IPS |
|
|
Image Classification (F16)
|
100% |
638
119.4 IPS |
|
|
Image Classification (I8)
|
97% |
1075
201.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
835
13.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
848
14.2 IPS |
|
|
Image Segmentation (I8)
|
98% |
973
16.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
1456
1.76 IPS |
|
|
Pose Estimation (F16)
|
100% |
1400
1.69 IPS |
|
|
Pose Estimation (I8)
|
100% |
6324
7.66 IPS |
|
|
Object Detection (F32)
|
100% |
634
47.3 IPS |
|
|
Object Detection (F16)
|
100% |
627
46.8 IPS |
|
|
Object Detection (I8)
|
61% |
1458
108.8 IPS |
|
|
Face Detection (F32)
|
100% |
1458
17.3 IPS |
|
|
Face Detection (F16)
|
100% |
1444
17.2 IPS |
|
|
Face Detection (I8)
|
86% |
2584
30.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
1444
11.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
1427
11.1 IPS |
|
|
Depth Estimation (I8)
|
95% |
2741
21.3 IPS |
|
|
Style Transfer (F32)
|
100% |
2513
3.31 IPS |
|
|
Style Transfer (F16)
|
100% |
2483
3.27 IPS |
|
|
Style Transfer (I8)
|
98% |
5148
6.77 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1016
36.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1058
37.8 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2707
96.7 IPS |
|
|
Text Classification (F32)
|
100% |
770
1.11 KIPS |
|
|
Text Classification (F16)
|
100% |
741
1.06 KIPS |
|
|
Text Classification (I8)
|
92% |
547
785.8 IPS |
|
|
Machine Translation (F32)
|
100% |
1499
27.6 IPS |
|
|
Machine Translation (F16)
|
100% |
1511
27.8 IPS |
|
|
Machine Translation (I8)
|
64% |
625
11.5 IPS |
