samsung SM-S936U1
Geekbench ML Score
1545
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 29 2025 03:16 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | samsung SM-S936U1 |
| Model ID | samsung SM-S936U1 |
| 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% |
678
126.8 IPS |
|
|
Image Classification (F16)
|
100% |
664
124.3 IPS |
|
|
Image Classification (I8)
|
100% |
791
148.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
894
14.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
1106
18.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
1108
18.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
1712
2.07 IPS |
|
|
Pose Estimation (F16)
|
100% |
2907
3.52 IPS |
|
|
Pose Estimation (I8)
|
100% |
2902
3.51 IPS |
|
|
Object Detection (F32)
|
100% |
421
31.4 IPS |
|
|
Object Detection (F16)
|
100% |
452
33.8 IPS |
|
|
Object Detection (I8)
|
59% |
515
38.4 IPS |
|
|
Face Detection (F32)
|
100% |
3180
37.8 IPS |
|
|
Face Detection (F16)
|
97% |
3494
41.5 IPS |
|
|
Face Detection (I8)
|
86% |
3761
44.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
1693
13.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
4985
38.7 IPS |
|
|
Depth Estimation (I8)
|
94% |
4766
37.0 IPS |
|
|
Style Transfer (F32)
|
100% |
6202
8.16 IPS |
|
|
Style Transfer (F16)
|
100% |
12927
17.0 IPS |
|
|
Style Transfer (I8)
|
98% |
12927
17.0 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
688
24.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1103
39.4 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1133
40.5 IPS |
|
|
Text Classification (F32)
|
100% |
661
950.1 IPS |
|
|
Text Classification (F16)
|
100% |
669
961.3 IPS |
|
|
Text Classification (I8)
|
92% |
1057
1.52 KIPS |
|
|
Machine Translation (F32)
|
100% |
1097
20.2 IPS |
|
|
Machine Translation (F16)
|
100% |
1076
19.8 IPS |
|
|
Machine Translation (I8)
|
64% |
1028
18.9 IPS |
