samsung SM-S938B
Geekbench ML Score
2081
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | February 04 2025 10:12 AM |
| Views | 3 |
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% |
1262
236.2 IPS |
|
|
Image Classification (F16)
|
100% |
1261
236.0 IPS |
|
|
Image Classification (I8)
|
97% |
1561
292.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
1677
28.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
1626
27.1 IPS |
|
|
Image Segmentation (I8)
|
98% |
1751
29.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
2245
2.72 IPS |
|
|
Pose Estimation (F16)
|
100% |
2114
2.56 IPS |
|
|
Pose Estimation (I8)
|
100% |
9046
11.0 IPS |
|
|
Object Detection (F32)
|
100% |
1223
91.3 IPS |
|
|
Object Detection (F16)
|
100% |
1150
85.8 IPS |
|
|
Object Detection (I8)
|
61% |
1972
147.2 IPS |
|
|
Face Detection (F32)
|
100% |
2440
29.0 IPS |
|
|
Face Detection (F16)
|
100% |
2392
28.4 IPS |
|
|
Face Detection (I8)
|
86% |
4486
53.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
2345
18.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
2275
17.6 IPS |
|
|
Depth Estimation (I8)
|
95% |
4161
32.3 IPS |
|
|
Style Transfer (F32)
|
100% |
3527
4.64 IPS |
|
|
Style Transfer (F16)
|
100% |
3497
4.60 IPS |
|
|
Style Transfer (I8)
|
98% |
10130
13.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1367
48.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1426
50.9 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
4148
148.1 IPS |
|
|
Text Classification (F32)
|
100% |
1140
1.64 KIPS |
|
|
Text Classification (F16)
|
100% |
1150
1.65 KIPS |
|
|
Text Classification (I8)
|
92% |
829
1.19 KIPS |
|
|
Machine Translation (F32)
|
100% |
2025
37.3 IPS |
|
|
Machine Translation (F16)
|
100% |
1977
36.4 IPS |
|
|
Machine Translation (I8)
|
64% |
993
18.3 IPS |
