Samsung Galaxy S22 Ultra
Geekbench ML Score
460
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 21 2024 01:09 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
312
58.4 IPS |
|
|
Image Classification (F16)
|
100% |
340
63.6 IPS |
|
|
Image Classification (I8)
|
97% |
551
103.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
289
4.83 IPS |
|
|
Image Segmentation (F16)
|
100% |
270
4.50 IPS |
|
|
Image Segmentation (I8)
|
98% |
293
4.89 IPS |
|
|
Pose Estimation (F32)
|
100% |
731
0.89 IPS |
|
|
Pose Estimation (F16)
|
100% |
695
0.84 IPS |
|
|
Pose Estimation (I8)
|
100% |
2922
3.54 IPS |
|
|
Object Detection (F32)
|
100% |
177
13.2 IPS |
|
|
Object Detection (F16)
|
100% |
150
11.2 IPS |
|
|
Object Detection (I8)
|
61% |
258
19.2 IPS |
|
|
Face Detection (F32)
|
100% |
383
4.55 IPS |
|
|
Face Detection (F16)
|
100% |
419
4.98 IPS |
|
|
Face Detection (I8)
|
86% |
545
6.48 IPS |
|
|
Depth Estimation (F32)
|
100% |
511
3.96 IPS |
|
|
Depth Estimation (F16)
|
100% |
477
3.70 IPS |
|
|
Depth Estimation (I8)
|
95% |
812
6.30 IPS |
|
|
Style Transfer (F32)
|
100% |
1348
1.77 IPS |
|
|
Style Transfer (F16)
|
100% |
1335
1.76 IPS |
|
|
Style Transfer (I8)
|
98% |
2654
3.49 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
456
16.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
576
20.6 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
388
13.9 IPS |
|
|
Text Classification (F32)
|
100% |
484
696.2 IPS |
|
|
Text Classification (F16)
|
100% |
494
709.3 IPS |
|
|
Text Classification (I8)
|
92% |
401
575.8 IPS |
|
|
Machine Translation (F32)
|
100% |
250
4.60 IPS |
|
|
Machine Translation (F16)
|
100% |
314
5.78 IPS |
|
|
Machine Translation (I8)
|
64% |
89
1.65 IPS |
