samsung SM-S928B
Geekbench ML Score
1133
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 09 2024 08:09 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-S928B |
| Model ID | samsung SM-S928B |
| 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% |
616
115.3 IPS |
|
|
Image Classification (F16)
|
100% |
615
115.0 IPS |
|
|
Image Classification (I8)
|
97% |
1028
192.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
789
13.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
767
12.8 IPS |
|
|
Image Segmentation (I8)
|
98% |
953
15.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
1281
1.55 IPS |
|
|
Pose Estimation (F16)
|
100% |
1358
1.64 IPS |
|
|
Pose Estimation (I8)
|
100% |
5858
7.09 IPS |
|
|
Object Detection (F32)
|
100% |
541
40.4 IPS |
|
|
Object Detection (F16)
|
100% |
514
38.4 IPS |
|
|
Object Detection (I8)
|
61% |
1182
88.3 IPS |
|
|
Face Detection (F32)
|
100% |
1138
13.5 IPS |
|
|
Face Detection (F16)
|
100% |
1169
13.9 IPS |
|
|
Face Detection (I8)
|
86% |
2211
26.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
1260
9.77 IPS |
|
|
Depth Estimation (F16)
|
100% |
1231
9.55 IPS |
|
|
Depth Estimation (I8)
|
95% |
2394
18.6 IPS |
|
|
Style Transfer (F32)
|
100% |
2369
3.12 IPS |
|
|
Style Transfer (F16)
|
100% |
2308
3.04 IPS |
|
|
Style Transfer (I8)
|
98% |
4672
6.15 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
812
29.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
831
29.7 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2181
77.9 IPS |
|
|
Text Classification (F32)
|
100% |
580
833.6 IPS |
|
|
Text Classification (F16)
|
100% |
585
840.5 IPS |
|
|
Text Classification (I8)
|
92% |
455
654.3 IPS |
|
|
Machine Translation (F32)
|
100% |
1339
24.6 IPS |
|
|
Machine Translation (F16)
|
100% |
1312
24.1 IPS |
|
|
Machine Translation (I8)
|
64% |
510
9.39 IPS |
