Samsung Galaxy S22
Geekbench ML Score
558
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 Corporate for Android AArch64
Result Information
| Upload Date | December 08 2023 03:33 PM |
| Views | 4 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Samsung Galaxy S22 |
| Model ID | samsung SM-S901W |
| 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 | 7.06 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
374
70.0 IPS |
|
|
Image Classification (F16)
|
100% |
351
65.7 IPS |
|
|
Image Classification (I8)
|
97% |
460
86.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
431
7.20 IPS |
|
|
Image Segmentation (F16)
|
100% |
408
6.81 IPS |
|
|
Image Segmentation (I8)
|
98% |
413
6.90 IPS |
|
|
Pose Estimation (F32)
|
100% |
803
0.97 IPS |
|
|
Pose Estimation (F16)
|
100% |
788
0.95 IPS |
|
|
Pose Estimation (I8)
|
100% |
2980
3.61 IPS |
|
|
Object Detection (F32)
|
100% |
96
7.13 IPS |
|
|
Object Detection (F16)
|
100% |
97
7.23 IPS |
|
|
Object Detection (I8)
|
61% |
112
8.39 IPS |
|
|
Face Detection (F32)
|
100% |
671
7.97 IPS |
|
|
Face Detection (F16)
|
100% |
673
8.00 IPS |
|
|
Face Detection (I8)
|
86% |
1083
12.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
761
5.90 IPS |
|
|
Depth Estimation (F16)
|
100% |
727
5.64 IPS |
|
|
Depth Estimation (I8)
|
95% |
1387
10.8 IPS |
|
|
Style Transfer (F32)
|
100% |
1572
2.07 IPS |
|
|
Style Transfer (F16)
|
100% |
1553
2.04 IPS |
|
|
Style Transfer (I8)
|
98% |
3539
4.66 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
495
17.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
476
17.0 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
988
35.3 IPS |
|
|
Text Classification (F32)
|
100% |
332
477.5 IPS |
|
|
Text Classification (F16)
|
100% |
401
576.4 IPS |
|
|
Text Classification (I8)
|
92% |
282
405.2 IPS |
|
|
Machine Translation (F32)
|
100% |
621
11.4 IPS |
|
|
Machine Translation (F16)
|
100% |
620
11.4 IPS |
|
|
Machine Translation (I8)
|
64% |
270
4.98 IPS |
