Samsung Galaxy S23
Geekbench ML Score
977
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 08 2024 11:56 AM |
| 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% |
486
90.9 IPS |
|
|
Image Classification (F16)
|
100% |
486
90.9 IPS |
|
|
Image Classification (I8)
|
97% |
865
161.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
596
9.95 IPS |
|
|
Image Segmentation (F16)
|
100% |
627
10.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
776
13.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
1087
1.32 IPS |
|
|
Pose Estimation (F16)
|
100% |
1088
1.32 IPS |
|
|
Pose Estimation (I8)
|
100% |
4379
5.30 IPS |
|
|
Object Detection (F32)
|
100% |
519
38.8 IPS |
|
|
Object Detection (F16)
|
100% |
503
37.6 IPS |
|
|
Object Detection (I8)
|
61% |
1144
85.4 IPS |
|
|
Face Detection (F32)
|
100% |
1090
13.0 IPS |
|
|
Face Detection (F16)
|
100% |
1065
12.7 IPS |
|
|
Face Detection (I8)
|
86% |
1682
20.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
1076
8.34 IPS |
|
|
Depth Estimation (F16)
|
100% |
1091
8.46 IPS |
|
|
Depth Estimation (I8)
|
95% |
2005
15.5 IPS |
|
|
Style Transfer (F32)
|
100% |
1880
2.47 IPS |
|
|
Style Transfer (F16)
|
100% |
2010
2.64 IPS |
|
|
Style Transfer (I8)
|
98% |
4318
5.68 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
671
24.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
670
23.9 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2081
74.3 IPS |
|
|
Text Classification (F32)
|
100% |
613
880.4 IPS |
|
|
Text Classification (F16)
|
100% |
568
815.8 IPS |
|
|
Text Classification (I8)
|
92% |
448
644.1 IPS |
|
|
Machine Translation (F32)
|
100% |
1024
18.8 IPS |
|
|
Machine Translation (F16)
|
100% |
1008
18.5 IPS |
|
|
Machine Translation (I8)
|
64% |
489
9.01 IPS |
