Samsung Galaxy S23 Ultra
Geekbench ML Score
1014
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 06 2024 06:11 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% |
514
96.1 IPS |
|
|
Image Classification (F16)
|
100% |
500
93.5 IPS |
|
|
Image Classification (I8)
|
97% |
876
164.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
624
10.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
639
10.7 IPS |
|
|
Image Segmentation (I8)
|
98% |
794
13.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
1146
1.39 IPS |
|
|
Pose Estimation (F16)
|
100% |
1107
1.34 IPS |
|
|
Pose Estimation (I8)
|
100% |
4528
5.48 IPS |
|
|
Object Detection (F32)
|
100% |
523
39.1 IPS |
|
|
Object Detection (F16)
|
100% |
523
39.1 IPS |
|
|
Object Detection (I8)
|
61% |
1161
86.7 IPS |
|
|
Face Detection (F32)
|
100% |
1058
12.6 IPS |
|
|
Face Detection (F16)
|
100% |
1103
13.1 IPS |
|
|
Face Detection (I8)
|
86% |
1833
21.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
1137
8.82 IPS |
|
|
Depth Estimation (F16)
|
100% |
1125
8.72 IPS |
|
|
Depth Estimation (I8)
|
95% |
2128
16.5 IPS |
|
|
Style Transfer (F32)
|
100% |
1963
2.58 IPS |
|
|
Style Transfer (F16)
|
100% |
1991
2.62 IPS |
|
|
Style Transfer (I8)
|
98% |
4333
5.70 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
718
25.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
753
26.9 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2091
74.7 IPS |
|
|
Text Classification (F32)
|
100% |
507
729.4 IPS |
|
|
Text Classification (F16)
|
100% |
660
948.4 IPS |
|
|
Text Classification (I8)
|
92% |
513
736.9 IPS |
|
|
Machine Translation (F32)
|
100% |
1116
20.5 IPS |
|
|
Machine Translation (F16)
|
100% |
1117
20.6 IPS |
|
|
Machine Translation (I8)
|
64% |
498
9.16 IPS |
