Samsung Galaxy S22 Ultra
Geekbench ML Score
299
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 27 2024 06:52 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S22 Ultra |
| Model ID | samsung SM-S908U1 |
| Motherboard | taro |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 2 part 3400 revision 0 |
| Base Frequency | 1.78 GHz |
| Cluster 1 | 4 Cores @ 1.79 GHz |
| Cluster 2 | 3 Cores @ 2.50 GHz |
| Cluster 3 | 1 Core @ 3.00 GHz |
| Memory Information | |
|---|---|
| Size | 7.06 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
151
28.3 IPS |
|
|
Image Classification (F16)
|
100% |
151
28.3 IPS |
|
|
Image Classification (I8)
|
97% |
415
77.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
182
3.04 IPS |
|
|
Image Segmentation (F16)
|
100% |
173
2.88 IPS |
|
|
Image Segmentation (I8)
|
98% |
375
6.27 IPS |
|
|
Pose Estimation (F32)
|
100% |
210
0.25 IPS |
|
|
Pose Estimation (F16)
|
100% |
212
0.26 IPS |
|
|
Pose Estimation (I8)
|
100% |
842
1.02 IPS |
|
|
Object Detection (F32)
|
100% |
127
9.48 IPS |
|
|
Object Detection (F16)
|
100% |
127
9.51 IPS |
|
|
Object Detection (I8)
|
61% |
367
27.4 IPS |
|
|
Face Detection (F32)
|
100% |
342
4.06 IPS |
|
|
Face Detection (F16)
|
100% |
342
4.07 IPS |
|
|
Face Detection (I8)
|
86% |
822
9.78 IPS |
|
|
Depth Estimation (F32)
|
100% |
279
2.17 IPS |
|
|
Depth Estimation (F16)
|
100% |
281
2.18 IPS |
|
|
Depth Estimation (I8)
|
95% |
818
6.34 IPS |
|
|
Style Transfer (F32)
|
100% |
489
0.64 IPS |
|
|
Style Transfer (F16)
|
100% |
491
0.65 IPS |
|
|
Style Transfer (I8)
|
98% |
1224
1.61 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
138
4.94 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
139
4.97 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
506
18.1 IPS |
|
|
Text Classification (F32)
|
100% |
164
235.4 IPS |
|
|
Text Classification (F16)
|
100% |
162
233.3 IPS |
|
|
Text Classification (I8)
|
92% |
310
445.2 IPS |
|
|
Machine Translation (F32)
|
100% |
309
5.69 IPS |
|
|
Machine Translation (F16)
|
100% |
360
6.63 IPS |
|
|
Machine Translation (I8)
|
64% |
473
8.70 IPS |
