samsung SM-S928U1
Geekbench ML Score
1138
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 08 2024 02:47 PM |
| Views | 3 |
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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
425
79.5 IPS |
|
|
Image Classification (F16)
|
100% |
496
92.8 IPS |
|
|
Image Classification (I8)
|
97% |
946
177.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
686
11.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
675
11.3 IPS |
|
|
Image Segmentation (I8)
|
98% |
815
13.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
1456
1.76 IPS |
|
|
Pose Estimation (F16)
|
100% |
1396
1.69 IPS |
|
|
Pose Estimation (I8)
|
100% |
5715
6.92 IPS |
|
|
Object Detection (F32)
|
100% |
531
39.6 IPS |
|
|
Object Detection (F16)
|
100% |
529
39.5 IPS |
|
|
Object Detection (I8)
|
61% |
1068
79.7 IPS |
|
|
Face Detection (F32)
|
100% |
1233
14.7 IPS |
|
|
Face Detection (F16)
|
100% |
1241
14.8 IPS |
|
|
Face Detection (I8)
|
86% |
2298
27.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
1304
10.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
1278
9.91 IPS |
|
|
Depth Estimation (I8)
|
95% |
2250
17.4 IPS |
|
|
Style Transfer (F32)
|
100% |
2548
3.35 IPS |
|
|
Style Transfer (F16)
|
100% |
2563
3.37 IPS |
|
|
Style Transfer (I8)
|
98% |
5167
6.80 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
936
33.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
956
34.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2462
87.9 IPS |
|
|
Text Classification (F32)
|
100% |
624
896.9 IPS |
|
|
Text Classification (F16)
|
100% |
577
829.5 IPS |
|
|
Text Classification (I8)
|
92% |
470
675.8 IPS |
|
|
Machine Translation (F32)
|
100% |
1410
25.9 IPS |
|
|
Machine Translation (F16)
|
100% |
1417
26.1 IPS |
|
|
Machine Translation (I8)
|
64% |
567
10.4 IPS |
