Samsung Galaxy S22 Ultra
Geekbench ML Score
596
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 08 2024 09:03 PM |
| 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
313
58.6 IPS |
|
|
Image Classification (F16)
|
100% |
306
57.2 IPS |
|
|
Image Classification (I8)
|
97% |
449
84.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
390
6.51 IPS |
|
|
Image Segmentation (F16)
|
100% |
395
6.60 IPS |
|
|
Image Segmentation (I8)
|
98% |
395
6.60 IPS |
|
|
Pose Estimation (F32)
|
100% |
693
0.84 IPS |
|
|
Pose Estimation (F16)
|
100% |
662
0.80 IPS |
|
|
Pose Estimation (I8)
|
100% |
2409
2.92 IPS |
|
|
Object Detection (F32)
|
100% |
291
21.7 IPS |
|
|
Object Detection (F16)
|
100% |
299
22.3 IPS |
|
|
Object Detection (I8)
|
61% |
562
41.9 IPS |
|
|
Face Detection (F32)
|
100% |
673
8.00 IPS |
|
|
Face Detection (F16)
|
100% |
711
8.45 IPS |
|
|
Face Detection (I8)
|
86% |
1038
12.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
698
5.41 IPS |
|
|
Depth Estimation (F16)
|
100% |
677
5.25 IPS |
|
|
Depth Estimation (I8)
|
95% |
1343
10.4 IPS |
|
|
Style Transfer (F32)
|
100% |
1309
1.72 IPS |
|
|
Style Transfer (F16)
|
100% |
1322
1.74 IPS |
|
|
Style Transfer (I8)
|
98% |
2811
3.70 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
428
15.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
421
15.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1167
41.7 IPS |
|
|
Text Classification (F32)
|
100% |
396
569.4 IPS |
|
|
Text Classification (F16)
|
100% |
416
598.2 IPS |
|
|
Text Classification (I8)
|
92% |
276
397.3 IPS |
|
|
Machine Translation (F32)
|
100% |
633
11.6 IPS |
|
|
Machine Translation (F16)
|
100% |
571
10.5 IPS |
|
|
Machine Translation (I8)
|
64% |
242
4.45 IPS |
