Samsung Galaxy S22 Ultra
Geekbench ML Score
471
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 25 2024 11:17 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 | 10.27 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
361
67.6 IPS |
|
|
Image Classification (F16)
|
100% |
316
59.1 IPS |
|
|
Image Classification (I8)
|
97% |
330
61.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
302
5.04 IPS |
|
|
Image Segmentation (F16)
|
100% |
267
4.45 IPS |
|
|
Image Segmentation (I8)
|
98% |
313
5.22 IPS |
|
|
Pose Estimation (F32)
|
100% |
759
0.92 IPS |
|
|
Pose Estimation (F16)
|
100% |
735
0.89 IPS |
|
|
Pose Estimation (I8)
|
100% |
2496
3.02 IPS |
|
|
Object Detection (F32)
|
100% |
200
14.9 IPS |
|
|
Object Detection (F16)
|
100% |
196
14.6 IPS |
|
|
Object Detection (I8)
|
61% |
478
35.7 IPS |
|
|
Face Detection (F32)
|
100% |
379
4.51 IPS |
|
|
Face Detection (F16)
|
100% |
372
4.43 IPS |
|
|
Face Detection (I8)
|
86% |
608
7.23 IPS |
|
|
Depth Estimation (F32)
|
100% |
464
3.60 IPS |
|
|
Depth Estimation (F16)
|
100% |
461
3.57 IPS |
|
|
Depth Estimation (I8)
|
95% |
918
7.12 IPS |
|
|
Style Transfer (F32)
|
100% |
1314
1.73 IPS |
|
|
Style Transfer (F16)
|
100% |
1268
1.67 IPS |
|
|
Style Transfer (I8)
|
98% |
2617
3.44 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
391
14.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
423
15.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
441
15.7 IPS |
|
|
Text Classification (F32)
|
100% |
516
741.5 IPS |
|
|
Text Classification (F16)
|
100% |
422
606.5 IPS |
|
|
Text Classification (I8)
|
92% |
286
410.6 IPS |
|
|
Machine Translation (F32)
|
100% |
342
6.30 IPS |
|
|
Machine Translation (F16)
|
100% |
350
6.43 IPS |
|
|
Machine Translation (I8)
|
64% |
165
3.04 IPS |
