Samsung Galaxy S10e
Geekbench ML Score
556
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 12 2024 06:57 AM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | Samsung Galaxy S10e |
| Model ID | samsung SM-G970U1 |
| Motherboard | msmnile |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | Qualcomm Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 13 part 2052 revision 14 |
| Base Frequency | 1.78 GHz |
| Cluster 1 | 4 Cores @ 1.79 GHz |
| Cluster 2 | 3 Cores @ 2.42 GHz |
| Cluster 3 | 1 Core @ 2.84 GHz |
| Memory Information | |
|---|---|
| Size | 5.34 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
423
79.2 IPS |
|
|
Image Classification (F16)
|
99% |
599
112.0 IPS |
|
|
Image Classification (I8)
|
97% |
1143
213.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
536
8.95 IPS |
|
|
Image Segmentation (F16)
|
100% |
692
11.6 IPS |
|
|
Image Segmentation (I8)
|
98% |
1043
17.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
1216
1.47 IPS |
|
|
Pose Estimation (F16)
|
100% |
2905
3.52 IPS |
|
|
Pose Estimation (I8)
|
100% |
10261
12.4 IPS |
|
|
Object Detection (F32)
|
100% |
402
30.0 IPS |
|
|
Object Detection (F16)
|
100% |
526
39.3 IPS |
|
|
Object Detection (I8)
|
59% |
961
71.8 IPS |
|
|
Face Detection (F32)
|
100% |
1124
13.4 IPS |
|
|
Face Detection (F16)
|
97% |
1507
17.9 IPS |
|
|
Face Detection (I8)
|
88% |
3104
36.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
490
3.80 IPS |
|
|
Depth Estimation (F16)
|
100% |
556
4.31 IPS |
|
|
Depth Estimation (I8)
|
82% |
6760
52.4 IPS |
|
|
Style Transfer (F32)
|
100% |
727
0.96 IPS |
|
|
Style Transfer (F16)
|
100% |
756
0.99 IPS |
|
|
Style Transfer (I8)
|
98% |
3532
4.65 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
744
26.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1414
50.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
4443
158.7 IPS |
|
|
Text Classification (F32)
|
64% |
8
11.1 IPS |
|
|
Text Classification (F16)
|
64% |
7
10.4 IPS |
|
|
Text Classification (I8)
|
92% |
71
101.5 IPS |
|
|
Machine Translation (F32)
|
100% |
227
4.19 IPS |
|
|
Machine Translation (F16)
|
100% |
349
6.42 IPS |
|
|
Machine Translation (I8)
|
0
|
