Samsung Galaxy S22 Ultra
Geekbench ML Score
243
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 04 2024 04:53 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S22 Ultra |
| Model ID | samsung SM-S908B |
| Motherboard | s5e9925 |
| Governor | energy_aware |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 2 part 3400 revision 0 |
| Base Frequency | 1.82 GHz |
| Cluster 1 | 4 Cores @ 1.82 GHz |
| Cluster 2 | 3 Cores @ 2.52 GHz |
| Cluster 3 | 1 Core @ 2.80 GHz |
| Memory Information | |
|---|---|
| Size | 7.12 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
131
24.6 IPS |
|
|
Image Classification (F16)
|
100% |
312
58.4 IPS |
|
|
Image Classification (I8)
|
97% |
371
69.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
378
6.31 IPS |
|
|
Image Segmentation (F16)
|
100% |
267
4.46 IPS |
|
|
Image Segmentation (I8)
|
98% |
328
5.48 IPS |
|
|
Pose Estimation (F32)
|
100% |
657
0.80 IPS |
|
|
Pose Estimation (F16)
|
100% |
638
0.77 IPS |
|
|
Pose Estimation (I8)
|
100% |
2723
3.30 IPS |
|
|
Object Detection (F32)
|
100% |
154
11.5 IPS |
|
|
Object Detection (F16)
|
100% |
209
15.6 IPS |
|
|
Object Detection (I8)
|
61% |
390
29.1 IPS |
|
|
Face Detection (F32)
|
100% |
392
4.66 IPS |
|
|
Face Detection (F16)
|
100% |
373
4.43 IPS |
|
|
Face Detection (I8)
|
86% |
555
6.60 IPS |
|
|
Depth Estimation (F32)
|
100% |
450
3.49 IPS |
|
|
Depth Estimation (F16)
|
100% |
426
3.31 IPS |
|
|
Depth Estimation (I8)
|
95% |
416
3.23 IPS |
|
|
Style Transfer (F32)
|
100% |
1142
1.50 IPS |
|
|
Style Transfer (F16)
|
100% |
1125
1.48 IPS |
|
|
Style Transfer (I8)
|
98% |
2236
2.94 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
187
6.69 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
187
6.68 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
251
8.95 IPS |
|
|
Text Classification (F32)
|
100% |
13
19.2 IPS |
|
|
Text Classification (F16)
|
100% |
14
19.7 IPS |
|
|
Text Classification (I8)
|
92% |
14
20.1 IPS |
|
|
Machine Translation (F32)
|
100% |
49
0.90 IPS |
|
|
Machine Translation (F16)
|
100% |
49
0.90 IPS |
|
|
Machine Translation (I8)
|
64% |
56
1.04 IPS |
