Samsung Galaxy S22 Ultra
Geekbench ML Score
641
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 18 2024 08:58 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S22 Ultra |
| Model ID | samsung SM-S908W |
| 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% |
267
50.0 IPS |
|
|
Image Classification (F16)
|
100% |
295
55.2 IPS |
|
|
Image Classification (I8)
|
97% |
538
100.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
422
7.06 IPS |
|
|
Image Segmentation (F16)
|
100% |
432
7.22 IPS |
|
|
Image Segmentation (I8)
|
98% |
597
9.98 IPS |
|
|
Pose Estimation (F32)
|
100% |
684
0.83 IPS |
|
|
Pose Estimation (F16)
|
100% |
653
0.79 IPS |
|
|
Pose Estimation (I8)
|
100% |
2502
3.03 IPS |
|
|
Object Detection (F32)
|
100% |
312
23.3 IPS |
|
|
Object Detection (F16)
|
100% |
309
23.1 IPS |
|
|
Object Detection (I8)
|
61% |
653
48.7 IPS |
|
|
Face Detection (F32)
|
100% |
702
8.35 IPS |
|
|
Face Detection (F16)
|
100% |
720
8.56 IPS |
|
|
Face Detection (I8)
|
86% |
1345
16.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
733
5.68 IPS |
|
|
Depth Estimation (F16)
|
100% |
715
5.55 IPS |
|
|
Depth Estimation (I8)
|
95% |
1374
10.7 IPS |
|
|
Style Transfer (F32)
|
100% |
1323
1.74 IPS |
|
|
Style Transfer (F16)
|
100% |
1285
1.69 IPS |
|
|
Style Transfer (I8)
|
98% |
2906
3.82 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
452
16.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
445
15.9 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1224
43.7 IPS |
|
|
Text Classification (F32)
|
100% |
410
589.3 IPS |
|
|
Text Classification (F16)
|
100% |
426
612.0 IPS |
|
|
Text Classification (I8)
|
92% |
314
451.8 IPS |
|
|
Machine Translation (F32)
|
100% |
676
12.4 IPS |
|
|
Machine Translation (F16)
|
100% |
680
12.5 IPS |
|
|
Machine Translation (I8)
|
64% |
331
6.09 IPS |
