samsung SM-S938B
Geekbench ML Score
1558
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | February 04 2025 10:22 AM |
| Views | 4 |
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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
722
135.1 IPS |
|
|
Image Classification (F16)
|
100% |
727
136.1 IPS |
|
|
Image Classification (I8)
|
100% |
801
149.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
968
16.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
1077
18.0 IPS |
|
|
Image Segmentation (I8)
|
98% |
1135
19.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
1661
2.01 IPS |
|
|
Pose Estimation (F16)
|
100% |
2864
3.47 IPS |
|
|
Pose Estimation (I8)
|
100% |
2894
3.50 IPS |
|
|
Object Detection (F32)
|
100% |
486
36.3 IPS |
|
|
Object Detection (F16)
|
100% |
553
41.3 IPS |
|
|
Object Detection (I8)
|
59% |
463
34.5 IPS |
|
|
Face Detection (F32)
|
100% |
3137
37.3 IPS |
|
|
Face Detection (F16)
|
97% |
3416
40.6 IPS |
|
|
Face Detection (I8)
|
86% |
3426
40.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
1657
12.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
4987
38.7 IPS |
|
|
Depth Estimation (I8)
|
94% |
5027
39.0 IPS |
|
|
Style Transfer (F32)
|
100% |
6191
8.14 IPS |
|
|
Style Transfer (F16)
|
100% |
12983
17.1 IPS |
|
|
Style Transfer (I8)
|
98% |
13041
17.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
677
24.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1136
40.6 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1137
40.6 IPS |
|
|
Text Classification (F32)
|
100% |
670
962.9 IPS |
|
|
Text Classification (F16)
|
100% |
665
955.6 IPS |
|
|
Text Classification (I8)
|
92% |
1058
1.52 KIPS |
|
|
Machine Translation (F32)
|
100% |
1068
19.7 IPS |
|
|
Machine Translation (F16)
|
100% |
1045
19.2 IPS |
|
|
Machine Translation (I8)
|
64% |
965
17.8 IPS |
