Samsung Galaxy S22 Ultra
Geekbench ML Score
565
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 27 2024 06:57 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S22 Ultra |
| Model ID | samsung SM-S908U1 |
| 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% |
285
53.3 IPS |
|
|
Image Classification (F16)
|
100% |
286
53.5 IPS |
|
|
Image Classification (I8)
|
97% |
397
74.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
396
6.62 IPS |
|
|
Image Segmentation (F16)
|
100% |
377
6.29 IPS |
|
|
Image Segmentation (I8)
|
98% |
488
8.14 IPS |
|
|
Pose Estimation (F32)
|
100% |
653
0.79 IPS |
|
|
Pose Estimation (F16)
|
100% |
582
0.70 IPS |
|
|
Pose Estimation (I8)
|
100% |
2564
3.10 IPS |
|
|
Object Detection (F32)
|
100% |
288
21.5 IPS |
|
|
Object Detection (F16)
|
100% |
300
22.4 IPS |
|
|
Object Detection (I8)
|
61% |
532
39.7 IPS |
|
|
Face Detection (F32)
|
100% |
662
7.87 IPS |
|
|
Face Detection (F16)
|
100% |
673
8.00 IPS |
|
|
Face Detection (I8)
|
86% |
1112
13.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
651
5.05 IPS |
|
|
Depth Estimation (F16)
|
100% |
648
5.02 IPS |
|
|
Depth Estimation (I8)
|
95% |
988
7.66 IPS |
|
|
Style Transfer (F32)
|
100% |
1184
1.56 IPS |
|
|
Style Transfer (F16)
|
100% |
1211
1.59 IPS |
|
|
Style Transfer (I8)
|
98% |
2611
3.44 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
376
13.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
393
14.0 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1106
39.5 IPS |
|
|
Text Classification (F32)
|
100% |
354
508.5 IPS |
|
|
Text Classification (F16)
|
100% |
374
537.1 IPS |
|
|
Text Classification (I8)
|
92% |
267
384.4 IPS |
|
|
Machine Translation (F32)
|
100% |
533
9.80 IPS |
|
|
Machine Translation (F16)
|
100% |
576
10.6 IPS |
|
|
Machine Translation (I8)
|
64% |
261
4.81 IPS |
