Samsung Galaxy S22 Ultra
Geekbench ML Score
416
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 08 2024 06:19 PM |
| 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% |
181
33.9 IPS |
|
|
Image Classification (F16)
|
100% |
180
33.8 IPS |
|
|
Image Classification (I8)
|
97% |
521
97.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
231
3.86 IPS |
|
|
Image Segmentation (F16)
|
100% |
231
3.86 IPS |
|
|
Image Segmentation (I8)
|
98% |
546
9.11 IPS |
|
|
Pose Estimation (F32)
|
100% |
307
0.37 IPS |
|
|
Pose Estimation (F16)
|
100% |
307
0.37 IPS |
|
|
Pose Estimation (I8)
|
100% |
1275
1.54 IPS |
|
|
Object Detection (F32)
|
100% |
188
14.1 IPS |
|
|
Object Detection (F16)
|
100% |
189
14.1 IPS |
|
|
Object Detection (I8)
|
61% |
564
42.1 IPS |
|
|
Face Detection (F32)
|
100% |
473
5.62 IPS |
|
|
Face Detection (F16)
|
100% |
472
5.61 IPS |
|
|
Face Detection (I8)
|
86% |
1193
14.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
388
3.01 IPS |
|
|
Depth Estimation (F16)
|
100% |
387
3.00 IPS |
|
|
Depth Estimation (I8)
|
95% |
1209
9.37 IPS |
|
|
Style Transfer (F32)
|
100% |
654
0.86 IPS |
|
|
Style Transfer (F16)
|
100% |
657
0.86 IPS |
|
|
Style Transfer (I8)
|
98% |
1722
2.26 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
205
7.30 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
205
7.32 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
806
28.8 IPS |
|
|
Text Classification (F32)
|
100% |
245
352.7 IPS |
|
|
Text Classification (F16)
|
100% |
245
352.2 IPS |
|
|
Text Classification (I8)
|
92% |
459
659.3 IPS |
|
|
Machine Translation (F32)
|
100% |
426
7.84 IPS |
|
|
Machine Translation (F16)
|
100% |
421
7.74 IPS |
|
|
Machine Translation (I8)
|
64% |
558
10.3 IPS |
