samsung SM-S928U
Geekbench ML Score
1295
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | August 28 2024 08:46 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-S928U |
| Model ID | samsung SM-S928U |
| 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% |
649
121.5 IPS |
|
|
Image Classification (F16)
|
100% |
631
118.1 IPS |
|
|
Image Classification (I8)
|
97% |
1074
201.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
834
13.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
850
14.2 IPS |
|
|
Image Segmentation (I8)
|
98% |
929
15.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
1453
1.76 IPS |
|
|
Pose Estimation (F16)
|
100% |
1434
1.74 IPS |
|
|
Pose Estimation (I8)
|
100% |
5540
6.71 IPS |
|
|
Object Detection (F32)
|
100% |
547
40.8 IPS |
|
|
Object Detection (F16)
|
100% |
611
45.6 IPS |
|
|
Object Detection (I8)
|
61% |
1376
102.7 IPS |
|
|
Face Detection (F32)
|
100% |
1450
17.2 IPS |
|
|
Face Detection (F16)
|
100% |
1432
17.0 IPS |
|
|
Face Detection (I8)
|
86% |
2567
30.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
1454
11.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
1432
11.1 IPS |
|
|
Depth Estimation (I8)
|
95% |
2741
21.3 IPS |
|
|
Style Transfer (F32)
|
100% |
2552
3.36 IPS |
|
|
Style Transfer (F16)
|
100% |
2537
3.34 IPS |
|
|
Style Transfer (I8)
|
98% |
5437
7.15 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1070
38.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1026
36.6 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2950
105.3 IPS |
|
|
Text Classification (F32)
|
100% |
818
1.18 KIPS |
|
|
Text Classification (F16)
|
100% |
772
1.11 KIPS |
|
|
Text Classification (I8)
|
92% |
513
737.5 IPS |
|
|
Machine Translation (F32)
|
100% |
1499
27.6 IPS |
|
|
Machine Translation (F16)
|
100% |
1530
28.2 IPS |
|
|
Machine Translation (I8)
|
64% |
595
11.0 IPS |
