samsung SM-S938U
Geekbench ML Score
2108
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | February 17 2025 06:15 AM |
| Views | 4 |
System Information
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | samsung SM-S938U |
| Model ID | samsung SM-S938U |
| Motherboard | sun |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | Qualcomm ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 3 part 1 revision 4 |
| Base Frequency | 3.53 GHz |
| Cluster 1 | 6 Cores @ 3.53 GHz |
| Cluster 2 | 2 Cores @ 4.47 GHz |
| Memory Information | |
|---|---|
| Size | 10.86 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1240
232.1 IPS |
|
|
Image Classification (F16)
|
100% |
1270
237.7 IPS |
|
|
Image Classification (I8)
|
97% |
1608
300.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
1644
27.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
1604
26.8 IPS |
|
|
Image Segmentation (I8)
|
98% |
1769
29.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
2230
2.70 IPS |
|
|
Pose Estimation (F16)
|
100% |
2156
2.61 IPS |
|
|
Pose Estimation (I8)
|
100% |
8982
10.9 IPS |
|
|
Object Detection (F32)
|
100% |
1250
93.4 IPS |
|
|
Object Detection (F16)
|
100% |
1266
94.5 IPS |
|
|
Object Detection (I8)
|
61% |
1928
143.9 IPS |
|
|
Face Detection (F32)
|
100% |
2388
28.4 IPS |
|
|
Face Detection (F16)
|
100% |
2322
27.6 IPS |
|
|
Face Detection (I8)
|
86% |
4584
54.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
2365
18.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
2324
18.0 IPS |
|
|
Depth Estimation (I8)
|
95% |
4390
34.0 IPS |
|
|
Style Transfer (F32)
|
100% |
3528
4.64 IPS |
|
|
Style Transfer (F16)
|
100% |
3554
4.68 IPS |
|
|
Style Transfer (I8)
|
98% |
10412
13.7 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1390
49.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1422
50.8 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
4712
168.3 IPS |
|
|
Text Classification (F32)
|
100% |
1143
1.64 KIPS |
|
|
Text Classification (F16)
|
100% |
1164
1.67 KIPS |
|
|
Text Classification (I8)
|
92% |
794
1.14 KIPS |
|
|
Machine Translation (F32)
|
100% |
2111
38.9 IPS |
|
|
Machine Translation (F16)
|
100% |
2049
37.7 IPS |
|
|
Machine Translation (I8)
|
64% |
991
18.2 IPS |
