Samsung Galaxy S22
Geekbench ML Score
730
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | March 28 2024 04:27 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S22 |
| Model ID | samsung SM-S901N |
| 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% |
476
89.0 IPS |
|
|
Image Classification (F16)
|
100% |
585
109.5 IPS |
|
|
Image Classification (I8)
|
97% |
363
68.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
710
11.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
923
15.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
850
14.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
652
0.79 IPS |
|
|
Pose Estimation (F16)
|
100% |
1192
1.44 IPS |
|
|
Pose Estimation (I8)
|
100% |
1202
1.46 IPS |
|
|
Object Detection (F32)
|
100% |
258
19.3 IPS |
|
|
Object Detection (F16)
|
100% |
243
18.2 IPS |
|
|
Object Detection (I8)
|
62% |
245
18.3 IPS |
|
|
Face Detection (F32)
|
100% |
1482
17.6 IPS |
|
|
Face Detection (F16)
|
97% |
2356
28.0 IPS |
|
|
Face Detection (I8)
|
87% |
1699
20.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
1077
8.36 IPS |
|
|
Depth Estimation (F16)
|
100% |
2397
18.6 IPS |
|
|
Depth Estimation (I8)
|
95% |
2425
18.8 IPS |
|
|
Style Transfer (F32)
|
100% |
2496
3.28 IPS |
|
|
Style Transfer (F16)
|
100% |
5060
6.66 IPS |
|
|
Style Transfer (I8)
|
98% |
5027
6.61 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
318
11.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
433
15.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
431
15.4 IPS |
|
|
Text Classification (F32)
|
100% |
193
277.4 IPS |
|
|
Text Classification (F16)
|
100% |
193
277.9 IPS |
|
|
Text Classification (I8)
|
92% |
352
506.6 IPS |
|
|
Machine Translation (F32)
|
100% |
358
6.58 IPS |
|
|
Machine Translation (F16)
|
100% |
359
6.61 IPS |
|
|
Machine Translation (I8)
|
64% |
433
7.97 IPS |
