Samsung Galaxy S22 Ultra
Geekbench ML Score
501
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | June 29 2024 04:04 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S22 Ultra |
| Model ID | samsung SM-S908E |
| 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
220
41.3 IPS |
|
|
Image Classification (F16)
|
100% |
224
41.9 IPS |
|
|
Image Classification (I8)
|
97% |
360
67.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
325
5.42 IPS |
|
|
Image Segmentation (F16)
|
100% |
312
5.21 IPS |
|
|
Image Segmentation (I8)
|
98% |
403
6.72 IPS |
|
|
Pose Estimation (F32)
|
100% |
616
0.75 IPS |
|
|
Pose Estimation (F16)
|
100% |
577
0.70 IPS |
|
|
Pose Estimation (I8)
|
100% |
2159
2.61 IPS |
|
|
Object Detection (F32)
|
100% |
235
17.6 IPS |
|
|
Object Detection (F16)
|
100% |
264
19.7 IPS |
|
|
Object Detection (I8)
|
61% |
465
34.7 IPS |
|
|
Face Detection (F32)
|
100% |
566
6.73 IPS |
|
|
Face Detection (F16)
|
100% |
571
6.78 IPS |
|
|
Face Detection (I8)
|
86% |
958
11.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
569
4.42 IPS |
|
|
Depth Estimation (F16)
|
100% |
561
4.35 IPS |
|
|
Depth Estimation (I8)
|
95% |
1144
8.87 IPS |
|
|
Style Transfer (F32)
|
100% |
1096
1.44 IPS |
|
|
Style Transfer (F16)
|
100% |
1104
1.45 IPS |
|
|
Style Transfer (I8)
|
98% |
2291
3.01 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
356
12.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
365
13.0 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
918
32.8 IPS |
|
|
Text Classification (F32)
|
100% |
331
475.7 IPS |
|
|
Text Classification (F16)
|
100% |
307
440.8 IPS |
|
|
Text Classification (I8)
|
92% |
226
324.7 IPS |
|
|
Machine Translation (F32)
|
100% |
561
10.3 IPS |
|
|
Machine Translation (F16)
|
100% |
488
8.98 IPS |
|
|
Machine Translation (I8)
|
64% |
271
5.00 IPS |
