samsung SM-S938B
Geekbench ML Score
2053
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | March 22 2025 09:55 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | samsung SM-S938B |
| Model ID | samsung SM-S938B |
| 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% |
1256
235.0 IPS |
|
|
Image Classification (F16)
|
100% |
1234
231.0 IPS |
|
|
Image Classification (I8)
|
97% |
1530
286.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
1611
26.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
1585
26.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
1710
28.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
2138
2.59 IPS |
|
|
Pose Estimation (F16)
|
100% |
2149
2.60 IPS |
|
|
Pose Estimation (I8)
|
100% |
8855
10.7 IPS |
|
|
Object Detection (F32)
|
100% |
1142
85.3 IPS |
|
|
Object Detection (F16)
|
100% |
1211
90.4 IPS |
|
|
Object Detection (I8)
|
61% |
1987
148.3 IPS |
|
|
Face Detection (F32)
|
100% |
2382
28.3 IPS |
|
|
Face Detection (F16)
|
100% |
2411
28.7 IPS |
|
|
Face Detection (I8)
|
86% |
4280
50.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
2294
17.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
2277
17.7 IPS |
|
|
Depth Estimation (I8)
|
95% |
4113
31.9 IPS |
|
|
Style Transfer (F32)
|
100% |
3480
4.58 IPS |
|
|
Style Transfer (F16)
|
100% |
3486
4.59 IPS |
|
|
Style Transfer (I8)
|
98% |
9752
12.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1342
47.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1294
46.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
4478
159.9 IPS |
|
|
Text Classification (F32)
|
100% |
1163
1.67 KIPS |
|
|
Text Classification (F16)
|
100% |
1143
1.64 KIPS |
|
|
Text Classification (I8)
|
92% |
863
1.24 KIPS |
|
|
Machine Translation (F32)
|
100% |
2002
36.8 IPS |
|
|
Machine Translation (F16)
|
100% |
2021
37.2 IPS |
|
|
Machine Translation (I8)
|
64% |
905
16.7 IPS |
