Samsung Galaxy Tab S7
Geekbench ML Score
673
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 15 2024 01:23 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Samsung Galaxy Tab S7 |
| Model ID | samsung SM-T875 |
| Motherboard | kona |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3341 revision 0 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.42 GHz |
| Cluster 3 | 1 Core @ 3.09 GHz |
| Memory Information | |
|---|---|
| Size | 7.46 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
411
76.9 IPS |
|
|
Image Classification (F16)
|
100% |
627
117.4 IPS |
|
|
Image Classification (I8)
|
97% |
801
149.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
606
10.1 IPS |
|
|
Image Segmentation (F16)
|
100% |
798
13.3 IPS |
|
|
Image Segmentation (I8)
|
98% |
908
15.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
1534
1.86 IPS |
|
|
Pose Estimation (F16)
|
100% |
5698
6.90 IPS |
|
|
Pose Estimation (I8)
|
100% |
11031
13.4 IPS |
|
|
Object Detection (F32)
|
100% |
430
32.1 IPS |
|
|
Object Detection (F16)
|
99% |
651
48.6 IPS |
|
|
Object Detection (I8)
|
59% |
1033
77.1 IPS |
|
|
Face Detection (F32)
|
100% |
1087
12.9 IPS |
|
|
Face Detection (F16)
|
97% |
1270
15.1 IPS |
|
|
Face Detection (I8)
|
88% |
3481
41.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
508
3.94 IPS |
|
|
Depth Estimation (F16)
|
100% |
592
4.59 IPS |
|
|
Depth Estimation (I8)
|
82% |
7177
55.7 IPS |
|
|
Style Transfer (F32)
|
100% |
780
1.03 IPS |
|
|
Style Transfer (F16)
|
100% |
829
1.09 IPS |
|
|
Style Transfer (I8)
|
98% |
3981
5.24 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
779
27.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1932
69.0 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
4746
169.5 IPS |
|
|
Text Classification (F32)
|
64% |
3
4.79 IPS |
|
|
Text Classification (F16)
|
64% |
3
4.66 IPS |
|
|
Text Classification (I8)
|
94% |
98
140.5 IPS |
|
|
Machine Translation (F32)
|
100% |
130
2.39 IPS |
|
|
Machine Translation (F16)
|
100% |
376
6.92 IPS |
|
|
Machine Translation (I8)
|
58% |
334
6.15 IPS |
