Samsung Galaxy S22 Ultra
Geekbench ML Score
501
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | August 30 2024 10:48 PM |
| Views | 2 |
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% |
316
59.1 IPS |
|
|
Image Classification (F16)
|
100% |
323
60.5 IPS |
|
|
Image Classification (I8)
|
97% |
341
63.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
282
4.70 IPS |
|
|
Image Segmentation (F16)
|
100% |
263
4.39 IPS |
|
|
Image Segmentation (I8)
|
98% |
299
5.00 IPS |
|
|
Pose Estimation (F32)
|
100% |
759
0.92 IPS |
|
|
Pose Estimation (F16)
|
100% |
764
0.92 IPS |
|
|
Pose Estimation (I8)
|
100% |
3054
3.70 IPS |
|
|
Object Detection (F32)
|
100% |
186
13.9 IPS |
|
|
Object Detection (F16)
|
100% |
188
14.1 IPS |
|
|
Object Detection (I8)
|
61% |
546
40.7 IPS |
|
|
Face Detection (F32)
|
100% |
391
4.65 IPS |
|
|
Face Detection (F16)
|
100% |
409
4.86 IPS |
|
|
Face Detection (I8)
|
86% |
556
6.61 IPS |
|
|
Depth Estimation (F32)
|
100% |
458
3.55 IPS |
|
|
Depth Estimation (F16)
|
100% |
487
3.78 IPS |
|
|
Depth Estimation (I8)
|
95% |
790
6.13 IPS |
|
|
Style Transfer (F32)
|
100% |
1350
1.78 IPS |
|
|
Style Transfer (F16)
|
100% |
1312
1.73 IPS |
|
|
Style Transfer (I8)
|
98% |
2665
3.51 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
353
12.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
586
20.9 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
741
26.5 IPS |
|
|
Text Classification (F32)
|
100% |
519
745.5 IPS |
|
|
Text Classification (F16)
|
100% |
531
763.2 IPS |
|
|
Text Classification (I8)
|
92% |
429
616.0 IPS |
|
|
Machine Translation (F32)
|
100% |
325
5.99 IPS |
|
|
Machine Translation (F16)
|
100% |
315
5.79 IPS |
|
|
Machine Translation (I8)
|
64% |
282
5.19 IPS |
