Samsung Galaxy S23 Plus
Geekbench ML Score
1042
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 21 2024 05:08 PM |
| Views | 2 |
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% |
505
94.5 IPS |
|
|
Image Classification (F16)
|
100% |
508
95.0 IPS |
|
|
Image Classification (I8)
|
97% |
874
163.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
661
11.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
639
10.7 IPS |
|
|
Image Segmentation (I8)
|
98% |
785
13.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
1172
1.42 IPS |
|
|
Pose Estimation (F16)
|
100% |
1183
1.43 IPS |
|
|
Pose Estimation (I8)
|
100% |
4999
6.05 IPS |
|
|
Object Detection (F32)
|
100% |
552
41.2 IPS |
|
|
Object Detection (F16)
|
100% |
569
42.5 IPS |
|
|
Object Detection (I8)
|
61% |
1112
83.0 IPS |
|
|
Face Detection (F32)
|
100% |
1130
13.4 IPS |
|
|
Face Detection (F16)
|
100% |
1119
13.3 IPS |
|
|
Face Detection (I8)
|
86% |
1966
23.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
1155
8.95 IPS |
|
|
Depth Estimation (F16)
|
100% |
1135
8.80 IPS |
|
|
Depth Estimation (I8)
|
95% |
2313
17.9 IPS |
|
|
Style Transfer (F32)
|
100% |
2120
2.79 IPS |
|
|
Style Transfer (F16)
|
100% |
2111
2.78 IPS |
|
|
Style Transfer (I8)
|
98% |
4248
5.59 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
782
27.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
798
28.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2001
71.5 IPS |
|
|
Text Classification (F32)
|
100% |
627
901.4 IPS |
|
|
Text Classification (F16)
|
100% |
637
914.8 IPS |
|
|
Text Classification (I8)
|
92% |
431
619.5 IPS |
|
|
Machine Translation (F32)
|
100% |
1204
22.2 IPS |
|
|
Machine Translation (F16)
|
100% |
1167
21.5 IPS |
|
|
Machine Translation (I8)
|
64% |
443
8.16 IPS |
