Samsung Galaxy S23 Ultra
Geekbench ML Score
966
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | October 11 2024 01:40 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S23 Ultra |
| Model ID | samsung SM-S918U |
| 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% |
496
92.8 IPS |
|
|
Image Classification (F16)
|
100% |
473
88.5 IPS |
|
|
Image Classification (I8)
|
97% |
867
162.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
611
10.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
597
9.97 IPS |
|
|
Image Segmentation (I8)
|
98% |
725
12.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
1123
1.36 IPS |
|
|
Pose Estimation (F16)
|
100% |
1027
1.24 IPS |
|
|
Pose Estimation (I8)
|
100% |
4607
5.58 IPS |
|
|
Object Detection (F32)
|
100% |
471
35.2 IPS |
|
|
Object Detection (F16)
|
100% |
526
39.2 IPS |
|
|
Object Detection (I8)
|
61% |
893
66.6 IPS |
|
|
Face Detection (F32)
|
100% |
1088
12.9 IPS |
|
|
Face Detection (F16)
|
100% |
1053
12.5 IPS |
|
|
Face Detection (I8)
|
86% |
1842
21.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
1089
8.44 IPS |
|
|
Depth Estimation (F16)
|
100% |
1088
8.44 IPS |
|
|
Depth Estimation (I8)
|
95% |
2047
15.9 IPS |
|
|
Style Transfer (F32)
|
100% |
1880
2.47 IPS |
|
|
Style Transfer (F16)
|
100% |
1819
2.39 IPS |
|
|
Style Transfer (I8)
|
98% |
4043
5.32 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
701
25.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
678
24.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1936
69.1 IPS |
|
|
Text Classification (F32)
|
100% |
599
860.5 IPS |
|
|
Text Classification (F16)
|
100% |
619
889.3 IPS |
|
|
Text Classification (I8)
|
92% |
439
631.5 IPS |
|
|
Machine Translation (F32)
|
100% |
1092
20.1 IPS |
|
|
Machine Translation (F16)
|
100% |
1019
18.7 IPS |
|
|
Machine Translation (I8)
|
64% |
478
8.79 IPS |
