Samsung Galaxy S22 Ultra
Geekbench ML Score
448
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 18 2024 09:29 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S22 Ultra |
| Model ID | samsung SM-S908U |
| 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 | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
198
37.0 IPS |
|
|
Image Classification (F16)
|
100% |
196
36.6 IPS |
|
|
Image Classification (I8)
|
97% |
551
103.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
248
4.14 IPS |
|
|
Image Segmentation (F16)
|
100% |
247
4.12 IPS |
|
|
Image Segmentation (I8)
|
98% |
578
9.66 IPS |
|
|
Pose Estimation (F32)
|
100% |
313
0.38 IPS |
|
|
Pose Estimation (F16)
|
100% |
314
0.38 IPS |
|
|
Pose Estimation (I8)
|
100% |
1337
1.62 IPS |
|
|
Object Detection (F32)
|
100% |
203
15.2 IPS |
|
|
Object Detection (F16)
|
100% |
204
15.2 IPS |
|
|
Object Detection (I8)
|
61% |
599
44.7 IPS |
|
|
Face Detection (F32)
|
100% |
534
6.35 IPS |
|
|
Face Detection (F16)
|
100% |
521
6.20 IPS |
|
|
Face Detection (I8)
|
86% |
1313
15.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
437
3.39 IPS |
|
|
Depth Estimation (F16)
|
100% |
434
3.36 IPS |
|
|
Depth Estimation (I8)
|
95% |
1332
10.3 IPS |
|
|
Style Transfer (F32)
|
100% |
700
0.92 IPS |
|
|
Style Transfer (F16)
|
100% |
694
0.91 IPS |
|
|
Style Transfer (I8)
|
98% |
1913
2.52 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
214
7.63 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
212
7.57 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
823
29.4 IPS |
|
|
Text Classification (F32)
|
100% |
269
386.6 IPS |
|
|
Text Classification (F16)
|
100% |
269
386.5 IPS |
|
|
Text Classification (I8)
|
92% |
490
703.5 IPS |
|
|
Machine Translation (F32)
|
100% |
464
8.55 IPS |
|
|
Machine Translation (F16)
|
100% |
454
8.35 IPS |
|
|
Machine Translation (I8)
|
64% |
596
11.0 IPS |
