Samsung Galaxy S23
Geekbench ML Score
903
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | October 09 2024 10:11 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S23 |
| Model ID | samsung SM-S911B |
| Motherboard | kalama |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3406 revision 0 |
| Base Frequency | 2.02 GHz |
| Cluster 1 | 3 Cores @ 2.02 GHz |
| Cluster 2 | 4 Cores @ 2.80 GHz |
| Cluster 3 | 1 Core @ 3.36 GHz |
| Memory Information | |
|---|---|
| Size | 6.89 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
492
92.0 IPS |
|
|
Image Classification (F16)
|
100% |
488
91.3 IPS |
|
|
Image Classification (I8)
|
97% |
940
175.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
573
9.57 IPS |
|
|
Image Segmentation (F16)
|
100% |
587
9.81 IPS |
|
|
Image Segmentation (I8)
|
98% |
731
12.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
1044
1.26 IPS |
|
|
Pose Estimation (F16)
|
100% |
1050
1.27 IPS |
|
|
Pose Estimation (I8)
|
100% |
4082
4.94 IPS |
|
|
Object Detection (F32)
|
100% |
503
37.5 IPS |
|
|
Object Detection (F16)
|
100% |
496
37.1 IPS |
|
|
Object Detection (I8)
|
61% |
1042
77.8 IPS |
|
|
Face Detection (F32)
|
100% |
1093
13.0 IPS |
|
|
Face Detection (F16)
|
100% |
1070
12.7 IPS |
|
|
Face Detection (I8)
|
86% |
1861
22.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
1063
8.24 IPS |
|
|
Depth Estimation (F16)
|
100% |
1011
7.84 IPS |
|
|
Depth Estimation (I8)
|
95% |
1987
15.4 IPS |
|
|
Style Transfer (F32)
|
100% |
1811
2.38 IPS |
|
|
Style Transfer (F16)
|
100% |
1828
2.40 IPS |
|
|
Style Transfer (I8)
|
98% |
3612
4.75 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
641
22.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
618
22.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1721
61.5 IPS |
|
|
Text Classification (F32)
|
100% |
447
642.5 IPS |
|
|
Text Classification (F16)
|
100% |
430
618.6 IPS |
|
|
Text Classification (I8)
|
92% |
281
404.0 IPS |
|
|
Machine Translation (F32)
|
100% |
956
17.6 IPS |
|
|
Machine Translation (F16)
|
100% |
943
17.4 IPS |
|
|
Machine Translation (I8)
|
64% |
405
7.45 IPS |
