Samsung Galaxy S22 Ultra
Geekbench ML Score
739
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 27 2024 06:42 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
459
85.8 IPS |
|
|
Image Classification (F16)
|
100% |
365
68.4 IPS |
|
|
Image Classification (I8)
|
97% |
352
65.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
758
12.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
921
15.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
838
14.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
689
0.83 IPS |
|
|
Pose Estimation (F16)
|
100% |
1249
1.51 IPS |
|
|
Pose Estimation (I8)
|
100% |
1259
1.52 IPS |
|
|
Object Detection (F32)
|
100% |
303
22.6 IPS |
|
|
Object Detection (F16)
|
100% |
246
18.4 IPS |
|
|
Object Detection (I8)
|
62% |
239
17.8 IPS |
|
|
Face Detection (F32)
|
100% |
1580
18.8 IPS |
|
|
Face Detection (F16)
|
97% |
1487
17.7 IPS |
|
|
Face Detection (I8)
|
87% |
1840
21.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
1097
8.51 IPS |
|
|
Depth Estimation (F16)
|
100% |
2530
19.6 IPS |
|
|
Depth Estimation (I8)
|
95% |
2490
19.3 IPS |
|
|
Style Transfer (F32)
|
100% |
2576
3.39 IPS |
|
|
Style Transfer (F16)
|
100% |
3755
4.94 IPS |
|
|
Style Transfer (I8)
|
98% |
4309
5.67 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
328
11.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
410
14.6 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
415
14.8 IPS |
|
|
Text Classification (F32)
|
100% |
242
347.6 IPS |
|
|
Text Classification (F16)
|
100% |
254
365.6 IPS |
|
|
Text Classification (I8)
|
92% |
488
701.3 IPS |
|
|
Machine Translation (F32)
|
100% |
412
7.58 IPS |
|
|
Machine Translation (F16)
|
100% |
398
7.32 IPS |
|
|
Machine Translation (I8)
|
64% |
504
9.27 IPS |
