Samsung Galaxy S23
Geekbench ML Score
1027
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 18 2024 02:43 PM |
| Views | 2 |
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% |
525
98.2 IPS |
|
|
Image Classification (F16)
|
100% |
521
97.6 IPS |
|
|
Image Classification (I8)
|
97% |
853
159.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
637
10.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
650
10.9 IPS |
|
|
Image Segmentation (I8)
|
98% |
762
12.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
1207
1.46 IPS |
|
|
Pose Estimation (F16)
|
100% |
1184
1.43 IPS |
|
|
Pose Estimation (I8)
|
100% |
4834
5.85 IPS |
|
|
Object Detection (F32)
|
100% |
530
39.5 IPS |
|
|
Object Detection (F16)
|
100% |
522
39.0 IPS |
|
|
Object Detection (I8)
|
61% |
1121
83.7 IPS |
|
|
Face Detection (F32)
|
100% |
1108
13.2 IPS |
|
|
Face Detection (F16)
|
100% |
1092
13.0 IPS |
|
|
Face Detection (I8)
|
86% |
1864
22.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
1175
9.11 IPS |
|
|
Depth Estimation (F16)
|
100% |
1134
8.80 IPS |
|
|
Depth Estimation (I8)
|
95% |
2136
16.6 IPS |
|
|
Style Transfer (F32)
|
100% |
1958
2.58 IPS |
|
|
Style Transfer (F16)
|
100% |
2011
2.64 IPS |
|
|
Style Transfer (I8)
|
98% |
4333
5.70 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
731
26.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
760
27.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2142
76.5 IPS |
|
|
Text Classification (F32)
|
100% |
630
905.0 IPS |
|
|
Text Classification (F16)
|
100% |
612
880.0 IPS |
|
|
Text Classification (I8)
|
92% |
453
651.4 IPS |
|
|
Machine Translation (F32)
|
100% |
1172
21.6 IPS |
|
|
Machine Translation (F16)
|
100% |
1110
20.4 IPS |
|
|
Machine Translation (I8)
|
64% |
482
8.87 IPS |
