Samsung Galaxy S23 Ultra
Geekbench ML Score
1022
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 07 2024 07:02 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S23 Ultra |
| Model ID | samsung SM-S918B |
| 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 | 10.77 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
493
92.3 IPS |
|
|
Image Classification (F16)
|
100% |
478
89.4 IPS |
|
|
Image Classification (I8)
|
97% |
855
160.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
651
10.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
662
11.1 IPS |
|
|
Image Segmentation (I8)
|
98% |
702
11.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
1143
1.38 IPS |
|
|
Pose Estimation (F16)
|
100% |
1156
1.40 IPS |
|
|
Pose Estimation (I8)
|
100% |
4433
5.37 IPS |
|
|
Object Detection (F32)
|
100% |
517
38.6 IPS |
|
|
Object Detection (F16)
|
100% |
528
39.4 IPS |
|
|
Object Detection (I8)
|
61% |
1148
85.7 IPS |
|
|
Face Detection (F32)
|
100% |
1075
12.8 IPS |
|
|
Face Detection (F16)
|
100% |
1093
13.0 IPS |
|
|
Face Detection (I8)
|
86% |
1884
22.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
1190
9.23 IPS |
|
|
Depth Estimation (F16)
|
100% |
1172
9.09 IPS |
|
|
Depth Estimation (I8)
|
95% |
2151
16.7 IPS |
|
|
Style Transfer (F32)
|
100% |
2052
2.70 IPS |
|
|
Style Transfer (F16)
|
100% |
2032
2.67 IPS |
|
|
Style Transfer (I8)
|
98% |
4365
5.74 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
806
28.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
770
27.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2122
75.8 IPS |
|
|
Text Classification (F32)
|
100% |
606
871.3 IPS |
|
|
Text Classification (F16)
|
100% |
615
884.0 IPS |
|
|
Text Classification (I8)
|
92% |
460
661.4 IPS |
|
|
Machine Translation (F32)
|
100% |
1177
21.7 IPS |
|
|
Machine Translation (F16)
|
100% |
1147
21.1 IPS |
|
|
Machine Translation (I8)
|
64% |
475
8.74 IPS |
