Samsung Galaxy S22 Ultra
Geekbench ML Score
672
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | February 23 2024 01:07 AM |
| 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% |
348
65.0 IPS |
|
|
Image Classification (F16)
|
100% |
316
59.2 IPS |
|
|
Image Classification (I8)
|
97% |
550
103.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
446
7.45 IPS |
|
|
Image Segmentation (F16)
|
100% |
448
7.48 IPS |
|
|
Image Segmentation (I8)
|
98% |
546
9.12 IPS |
|
|
Pose Estimation (F32)
|
100% |
770
0.93 IPS |
|
|
Pose Estimation (F16)
|
100% |
755
0.91 IPS |
|
|
Pose Estimation (I8)
|
100% |
2805
3.40 IPS |
|
|
Object Detection (F32)
|
100% |
313
23.3 IPS |
|
|
Object Detection (F16)
|
100% |
314
23.4 IPS |
|
|
Object Detection (I8)
|
61% |
709
52.9 IPS |
|
|
Face Detection (F32)
|
100% |
766
9.11 IPS |
|
|
Face Detection (F16)
|
100% |
769
9.15 IPS |
|
|
Face Detection (I8)
|
86% |
1374
16.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
765
5.93 IPS |
|
|
Depth Estimation (F16)
|
100% |
738
5.72 IPS |
|
|
Depth Estimation (I8)
|
95% |
1494
11.6 IPS |
|
|
Style Transfer (F32)
|
100% |
1432
1.88 IPS |
|
|
Style Transfer (F16)
|
100% |
1392
1.83 IPS |
|
|
Style Transfer (I8)
|
98% |
2916
3.84 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
519
18.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
447
16.0 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1116
39.9 IPS |
|
|
Text Classification (F32)
|
100% |
400
574.7 IPS |
|
|
Text Classification (F16)
|
100% |
409
588.3 IPS |
|
|
Text Classification (I8)
|
92% |
341
490.1 IPS |
|
|
Machine Translation (F32)
|
100% |
706
13.0 IPS |
|
|
Machine Translation (F16)
|
100% |
685
12.6 IPS |
|
|
Machine Translation (I8)
|
64% |
333
6.13 IPS |
