Samsung Galaxy S23
Geekbench ML Score
1020
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 06 2024 06:19 AM |
| 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% |
498
93.2 IPS |
|
|
Image Classification (F16)
|
100% |
495
92.6 IPS |
|
|
Image Classification (I8)
|
97% |
633
118.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
599
10.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
632
10.6 IPS |
|
|
Image Segmentation (I8)
|
98% |
655
10.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
1120
1.36 IPS |
|
|
Pose Estimation (F16)
|
100% |
1112
1.35 IPS |
|
|
Pose Estimation (I8)
|
100% |
4792
5.80 IPS |
|
|
Object Detection (F32)
|
100% |
492
36.7 IPS |
|
|
Object Detection (F16)
|
100% |
527
39.4 IPS |
|
|
Object Detection (I8)
|
61% |
1183
88.3 IPS |
|
|
Face Detection (F32)
|
100% |
1082
12.9 IPS |
|
|
Face Detection (F16)
|
100% |
1094
13.0 IPS |
|
|
Face Detection (I8)
|
86% |
1808
21.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
1093
8.47 IPS |
|
|
Depth Estimation (F16)
|
100% |
1110
8.61 IPS |
|
|
Depth Estimation (I8)
|
95% |
2122
16.5 IPS |
|
|
Style Transfer (F32)
|
100% |
1870
2.46 IPS |
|
|
Style Transfer (F16)
|
100% |
2003
2.63 IPS |
|
|
Style Transfer (I8)
|
98% |
4179
5.50 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
761
27.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
769
27.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2392
85.4 IPS |
|
|
Text Classification (F32)
|
100% |
705
1.01 KIPS |
|
|
Text Classification (F16)
|
100% |
731
1.05 KIPS |
|
|
Text Classification (I8)
|
92% |
542
778.7 IPS |
|
|
Machine Translation (F32)
|
100% |
1322
24.3 IPS |
|
|
Machine Translation (F16)
|
100% |
1186
21.8 IPS |
|
|
Machine Translation (I8)
|
64% |
495
9.11 IPS |
