Samsung Galaxy S23 Ultra
Geekbench ML Score
1049
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | February 11 2025 10:23 PM |
| Views | 3 |
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% |
471
88.2 IPS |
|
|
Image Classification (F16)
|
100% |
467
87.3 IPS |
|
|
Image Classification (I8)
|
97% |
997
186.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
589
9.83 IPS |
|
|
Image Segmentation (F16)
|
100% |
615
10.3 IPS |
|
|
Image Segmentation (I8)
|
98% |
766
12.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
1059
1.28 IPS |
|
|
Pose Estimation (F16)
|
100% |
1044
1.26 IPS |
|
|
Pose Estimation (I8)
|
100% |
5176
6.27 IPS |
|
|
Object Detection (F32)
|
100% |
563
42.0 IPS |
|
|
Object Detection (F16)
|
100% |
540
40.3 IPS |
|
|
Object Detection (I8)
|
61% |
1272
95.0 IPS |
|
|
Face Detection (F32)
|
100% |
1086
12.9 IPS |
|
|
Face Detection (F16)
|
100% |
1083
12.9 IPS |
|
|
Face Detection (I8)
|
86% |
2166
25.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
1144
8.87 IPS |
|
|
Depth Estimation (F16)
|
100% |
1106
8.58 IPS |
|
|
Depth Estimation (I8)
|
95% |
2387
18.5 IPS |
|
|
Style Transfer (F32)
|
100% |
1919
2.52 IPS |
|
|
Style Transfer (F16)
|
100% |
1901
2.50 IPS |
|
|
Style Transfer (I8)
|
98% |
4195
5.52 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
789
28.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
795
28.4 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2309
82.5 IPS |
|
|
Text Classification (F32)
|
100% |
687
986.7 IPS |
|
|
Text Classification (F16)
|
100% |
684
983.4 IPS |
|
|
Text Classification (I8)
|
92% |
503
722.7 IPS |
|
|
Machine Translation (F32)
|
100% |
1219
22.4 IPS |
|
|
Machine Translation (F16)
|
100% |
1296
23.9 IPS |
|
|
Machine Translation (I8)
|
64% |
504
9.28 IPS |
