Samsung Galaxy S22 Ultra
Geekbench ML Score
816
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | February 23 2024 01:12 AM |
| Views | 1 |
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 | 10.95 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
373
69.9 IPS |
|
|
Image Classification (F16)
|
100% |
379
71.0 IPS |
|
|
Image Classification (I8)
|
97% |
520
97.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
718
12.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
884
14.8 IPS |
|
|
Image Segmentation (I8)
|
98% |
865
14.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
670
0.81 IPS |
|
|
Pose Estimation (F16)
|
100% |
1207
1.46 IPS |
|
|
Pose Estimation (I8)
|
100% |
1242
1.50 IPS |
|
|
Object Detection (F32)
|
100% |
252
18.8 IPS |
|
|
Object Detection (F16)
|
100% |
263
19.7 IPS |
|
|
Object Detection (I8)
|
62% |
392
29.2 IPS |
|
|
Face Detection (F32)
|
100% |
1674
19.9 IPS |
|
|
Face Detection (F16)
|
97% |
2317
27.6 IPS |
|
|
Face Detection (I8)
|
87% |
2231
26.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
1097
8.51 IPS |
|
|
Depth Estimation (F16)
|
100% |
2453
19.0 IPS |
|
|
Depth Estimation (I8)
|
95% |
2456
19.0 IPS |
|
|
Style Transfer (F32)
|
100% |
2698
3.55 IPS |
|
|
Style Transfer (F16)
|
100% |
5089
6.69 IPS |
|
|
Style Transfer (I8)
|
98% |
6084
8.00 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
383
13.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
519
18.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
515
18.4 IPS |
|
|
Text Classification (F32)
|
100% |
270
387.6 IPS |
|
|
Text Classification (F16)
|
100% |
269
386.4 IPS |
|
|
Text Classification (I8)
|
92% |
489
702.3 IPS |
|
|
Machine Translation (F32)
|
100% |
463
8.52 IPS |
|
|
Machine Translation (F16)
|
100% |
454
8.35 IPS |
|
|
Machine Translation (I8)
|
64% |
596
11.0 IPS |
