Samsung Galaxy S22
Geekbench ML Score
579
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 06 2024 08:28 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S22 |
| Model ID | samsung SM-S9010 |
| 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% |
294
55.1 IPS |
|
|
Image Classification (F16)
|
100% |
287
53.7 IPS |
|
|
Image Classification (I8)
|
97% |
416
77.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
387
6.47 IPS |
|
|
Image Segmentation (F16)
|
100% |
380
6.35 IPS |
|
|
Image Segmentation (I8)
|
98% |
437
7.29 IPS |
|
|
Pose Estimation (F32)
|
100% |
661
0.80 IPS |
|
|
Pose Estimation (F16)
|
100% |
625
0.76 IPS |
|
|
Pose Estimation (I8)
|
100% |
2580
3.12 IPS |
|
|
Object Detection (F32)
|
100% |
298
22.3 IPS |
|
|
Object Detection (F16)
|
100% |
268
20.0 IPS |
|
|
Object Detection (I8)
|
61% |
616
46.0 IPS |
|
|
Face Detection (F32)
|
100% |
651
7.74 IPS |
|
|
Face Detection (F16)
|
100% |
663
7.88 IPS |
|
|
Face Detection (I8)
|
86% |
984
11.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
670
5.20 IPS |
|
|
Depth Estimation (F16)
|
100% |
646
5.01 IPS |
|
|
Depth Estimation (I8)
|
95% |
1146
8.88 IPS |
|
|
Style Transfer (F32)
|
100% |
1207
1.59 IPS |
|
|
Style Transfer (F16)
|
100% |
1227
1.61 IPS |
|
|
Style Transfer (I8)
|
98% |
2703
3.56 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
403
14.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
431
15.4 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1208
43.1 IPS |
|
|
Text Classification (F32)
|
100% |
381
547.4 IPS |
|
|
Text Classification (F16)
|
100% |
391
561.5 IPS |
|
|
Text Classification (I8)
|
92% |
281
403.7 IPS |
|
|
Machine Translation (F32)
|
100% |
617
11.4 IPS |
|
|
Machine Translation (F16)
|
100% |
566
10.4 IPS |
|
|
Machine Translation (I8)
|
64% |
251
4.61 IPS |
