Samsung Galaxy S22 Ultra
Geekbench ML Score
441
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | February 23 2024 01:18 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S22 Ultra |
| Model ID | samsung SM-S908E |
| 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 | 10.95 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
197
36.9 IPS |
|
|
Image Classification (F16)
|
100% |
193
36.2 IPS |
|
|
Image Classification (I8)
|
97% |
551
103.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
241
4.03 IPS |
|
|
Image Segmentation (F16)
|
100% |
238
3.97 IPS |
|
|
Image Segmentation (I8)
|
98% |
570
9.51 IPS |
|
|
Pose Estimation (F32)
|
100% |
332
0.40 IPS |
|
|
Pose Estimation (F16)
|
100% |
328
0.40 IPS |
|
|
Pose Estimation (I8)
|
100% |
1330
1.61 IPS |
|
|
Object Detection (F32)
|
100% |
197
14.7 IPS |
|
|
Object Detection (F16)
|
100% |
199
14.9 IPS |
|
|
Object Detection (I8)
|
61% |
600
44.8 IPS |
|
|
Face Detection (F32)
|
100% |
518
6.16 IPS |
|
|
Face Detection (F16)
|
100% |
508
6.04 IPS |
|
|
Face Detection (I8)
|
86% |
1292
15.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
424
3.29 IPS |
|
|
Depth Estimation (F16)
|
100% |
421
3.26 IPS |
|
|
Depth Estimation (I8)
|
95% |
1277
9.90 IPS |
|
|
Style Transfer (F32)
|
100% |
684
0.90 IPS |
|
|
Style Transfer (F16)
|
100% |
678
0.89 IPS |
|
|
Style Transfer (I8)
|
98% |
1858
2.44 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
207
7.40 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
208
7.42 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
813
29.0 IPS |
|
|
Text Classification (F32)
|
100% |
268
385.3 IPS |
|
|
Text Classification (F16)
|
100% |
269
387.1 IPS |
|
|
Text Classification (I8)
|
92% |
488
701.9 IPS |
|
|
Machine Translation (F32)
|
100% |
453
8.34 IPS |
|
|
Machine Translation (F16)
|
100% |
446
8.20 IPS |
|
|
Machine Translation (I8)
|
64% |
578
10.6 IPS |
