samsung SM-S928U1
Geekbench ML Score
1191
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | August 23 2024 05:00 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
554
103.6 IPS |
|
|
Image Classification (F16)
|
100% |
563
105.4 IPS |
|
|
Image Classification (I8)
|
97% |
1036
193.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
799
13.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
775
12.9 IPS |
|
|
Image Segmentation (I8)
|
98% |
921
15.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
1365
1.65 IPS |
|
|
Pose Estimation (F16)
|
100% |
1362
1.65 IPS |
|
|
Pose Estimation (I8)
|
100% |
5824
7.05 IPS |
|
|
Object Detection (F32)
|
100% |
583
43.5 IPS |
|
|
Object Detection (F16)
|
100% |
616
46.0 IPS |
|
|
Object Detection (I8)
|
61% |
1391
103.8 IPS |
|
|
Face Detection (F32)
|
100% |
1413
16.8 IPS |
|
|
Face Detection (F16)
|
100% |
1386
16.5 IPS |
|
|
Face Detection (I8)
|
86% |
2349
27.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
1238
9.60 IPS |
|
|
Depth Estimation (F16)
|
100% |
1245
9.66 IPS |
|
|
Depth Estimation (I8)
|
95% |
2377
18.4 IPS |
|
|
Style Transfer (F32)
|
100% |
2456
3.23 IPS |
|
|
Style Transfer (F16)
|
100% |
2416
3.18 IPS |
|
|
Style Transfer (I8)
|
98% |
5331
7.01 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
918
32.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
933
33.3 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2324
83.0 IPS |
|
|
Text Classification (F32)
|
100% |
598
859.2 IPS |
|
|
Text Classification (F16)
|
100% |
593
852.1 IPS |
|
|
Text Classification (I8)
|
92% |
434
624.2 IPS |
|
|
Machine Translation (F32)
|
100% |
1450
26.7 IPS |
|
|
Machine Translation (F16)
|
100% |
1438
26.5 IPS |
|
|
Machine Translation (I8)
|
64% |
570
10.5 IPS |
