Samsung Galaxy S22 Ultra
Geekbench ML Score
258
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 04 2024 11:52 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S22 Ultra |
| Model ID | samsung SM-S908B |
| Motherboard | s5e9925 |
| Governor | energy_aware |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 2 part 3400 revision 0 |
| Base Frequency | 1.82 GHz |
| Cluster 1 | 4 Cores @ 1.82 GHz |
| Cluster 2 | 3 Cores @ 2.52 GHz |
| Cluster 3 | 1 Core @ 2.80 GHz |
| Memory Information | |
|---|---|
| Size | 7.12 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
111
20.7 IPS |
|
|
Image Classification (F16)
|
100% |
108
20.3 IPS |
|
|
Image Classification (I8)
|
97% |
294
55.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
136
2.27 IPS |
|
|
Image Segmentation (F16)
|
100% |
139
2.32 IPS |
|
|
Image Segmentation (I8)
|
98% |
304
5.07 IPS |
|
|
Pose Estimation (F32)
|
100% |
195
0.24 IPS |
|
|
Pose Estimation (F16)
|
100% |
179
0.22 IPS |
|
|
Pose Estimation (I8)
|
100% |
734
0.89 IPS |
|
|
Object Detection (F32)
|
100% |
108
8.03 IPS |
|
|
Object Detection (F16)
|
100% |
107
8.01 IPS |
|
|
Object Detection (I8)
|
61% |
321
24.0 IPS |
|
|
Face Detection (F32)
|
100% |
331
3.93 IPS |
|
|
Face Detection (F16)
|
100% |
324
3.85 IPS |
|
|
Face Detection (I8)
|
86% |
685
8.15 IPS |
|
|
Depth Estimation (F32)
|
100% |
280
2.17 IPS |
|
|
Depth Estimation (F16)
|
100% |
241
1.87 IPS |
|
|
Depth Estimation (I8)
|
95% |
703
5.45 IPS |
|
|
Style Transfer (F32)
|
100% |
422
0.56 IPS |
|
|
Style Transfer (F16)
|
100% |
450
0.59 IPS |
|
|
Style Transfer (I8)
|
98% |
1084
1.43 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
117
4.19 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
134
4.77 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
523
18.7 IPS |
|
|
Text Classification (F32)
|
100% |
160
230.6 IPS |
|
|
Text Classification (F16)
|
100% |
159
227.9 IPS |
|
|
Text Classification (I8)
|
92% |
309
444.2 IPS |
|
|
Machine Translation (F32)
|
100% |
264
4.85 IPS |
|
|
Machine Translation (F16)
|
100% |
289
5.33 IPS |
|
|
Machine Translation (I8)
|
64% |
354
6.52 IPS |
