Samsung Galaxy S23 Plus
Geekbench ML Score
1046
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 17 2024 04:15 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S23 Plus |
| Model ID | samsung SM-S916B |
| 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
98.3 IPS |
|
|
Image Classification (F16)
|
100% |
525
98.2 IPS |
|
|
Image Classification (I8)
|
97% |
874
163.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
636
10.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
644
10.7 IPS |
|
|
Image Segmentation (I8)
|
98% |
777
13.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
1190
1.44 IPS |
|
|
Pose Estimation (F16)
|
100% |
1198
1.45 IPS |
|
|
Pose Estimation (I8)
|
100% |
5140
6.22 IPS |
|
|
Object Detection (F32)
|
100% |
550
41.1 IPS |
|
|
Object Detection (F16)
|
100% |
545
40.7 IPS |
|
|
Object Detection (I8)
|
61% |
1193
89.0 IPS |
|
|
Face Detection (F32)
|
100% |
1114
13.2 IPS |
|
|
Face Detection (F16)
|
100% |
1112
13.2 IPS |
|
|
Face Detection (I8)
|
86% |
2008
23.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
1165
9.03 IPS |
|
|
Depth Estimation (F16)
|
100% |
1183
9.17 IPS |
|
|
Depth Estimation (I8)
|
95% |
2227
17.3 IPS |
|
|
Style Transfer (F32)
|
100% |
2079
2.73 IPS |
|
|
Style Transfer (F16)
|
100% |
2030
2.67 IPS |
|
|
Style Transfer (I8)
|
98% |
4419
5.81 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
773
27.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
740
26.4 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2076
74.1 IPS |
|
|
Text Classification (F32)
|
100% |
593
851.7 IPS |
|
|
Text Classification (F16)
|
100% |
648
930.8 IPS |
|
|
Text Classification (I8)
|
92% |
455
653.4 IPS |
|
|
Machine Translation (F32)
|
100% |
1241
22.8 IPS |
|
|
Machine Translation (F16)
|
100% |
1149
21.2 IPS |
|
|
Machine Translation (I8)
|
64% |
465
8.56 IPS |
