Samsung Galaxy S23 Ultra
Geekbench ML Score
937
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 09 2024 09:14 PM |
| Views | 1 |
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% |
454
84.9 IPS |
|
|
Image Classification (F16)
|
100% |
477
89.3 IPS |
|
|
Image Classification (I8)
|
97% |
787
147.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
612
10.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
587
9.81 IPS |
|
|
Image Segmentation (I8)
|
98% |
754
12.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
1052
1.27 IPS |
|
|
Pose Estimation (F16)
|
100% |
1115
1.35 IPS |
|
|
Pose Estimation (I8)
|
100% |
4191
5.07 IPS |
|
|
Object Detection (F32)
|
100% |
505
37.7 IPS |
|
|
Object Detection (F16)
|
100% |
480
35.8 IPS |
|
|
Object Detection (I8)
|
61% |
985
73.5 IPS |
|
|
Face Detection (F32)
|
100% |
1049
12.5 IPS |
|
|
Face Detection (F16)
|
100% |
1034
12.3 IPS |
|
|
Face Detection (I8)
|
86% |
1723
20.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
1071
8.30 IPS |
|
|
Depth Estimation (F16)
|
100% |
1072
8.31 IPS |
|
|
Depth Estimation (I8)
|
95% |
1838
14.3 IPS |
|
|
Style Transfer (F32)
|
100% |
1893
2.49 IPS |
|
|
Style Transfer (F16)
|
100% |
1803
2.37 IPS |
|
|
Style Transfer (I8)
|
98% |
4097
5.39 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
670
23.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
687
24.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1871
66.8 IPS |
|
|
Text Classification (F32)
|
100% |
474
681.7 IPS |
|
|
Text Classification (F16)
|
100% |
594
853.6 IPS |
|
|
Text Classification (I8)
|
92% |
452
650.1 IPS |
|
|
Machine Translation (F32)
|
100% |
1005
18.5 IPS |
|
|
Machine Translation (F16)
|
100% |
951
17.5 IPS |
|
|
Machine Translation (I8)
|
64% |
464
8.54 IPS |
