Samsung Galaxy S23 Ultra
Geekbench ML Score
1036
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | March 28 2024 03:50 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S23 Ultra |
| Model ID | samsung SM-S918N |
| 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% |
530
99.2 IPS |
|
|
Image Classification (F16)
|
100% |
526
98.4 IPS |
|
|
Image Classification (I8)
|
97% |
907
169.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
671
11.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
626
10.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
781
13.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
1193
1.44 IPS |
|
|
Pose Estimation (F16)
|
100% |
1173
1.42 IPS |
|
|
Pose Estimation (I8)
|
100% |
4816
5.83 IPS |
|
|
Object Detection (F32)
|
100% |
525
39.2 IPS |
|
|
Object Detection (F16)
|
100% |
521
38.9 IPS |
|
|
Object Detection (I8)
|
61% |
1196
89.3 IPS |
|
|
Face Detection (F32)
|
100% |
1126
13.4 IPS |
|
|
Face Detection (F16)
|
100% |
1147
13.6 IPS |
|
|
Face Detection (I8)
|
86% |
1860
22.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
1189
9.22 IPS |
|
|
Depth Estimation (F16)
|
100% |
1139
8.83 IPS |
|
|
Depth Estimation (I8)
|
95% |
2167
16.8 IPS |
|
|
Style Transfer (F32)
|
100% |
2046
2.69 IPS |
|
|
Style Transfer (F16)
|
100% |
2033
2.67 IPS |
|
|
Style Transfer (I8)
|
98% |
4311
5.67 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
763
27.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
733
26.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1847
66.0 IPS |
|
|
Text Classification (F32)
|
100% |
646
928.3 IPS |
|
|
Text Classification (F16)
|
100% |
623
895.9 IPS |
|
|
Text Classification (I8)
|
92% |
485
697.2 IPS |
|
|
Machine Translation (F32)
|
100% |
1177
21.7 IPS |
|
|
Machine Translation (F16)
|
100% |
1125
20.7 IPS |
|
|
Machine Translation (I8)
|
64% |
477
8.78 IPS |
