Samsung Galaxy S23 Ultra
Geekbench ML Score
1019
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 04 2024 11:04 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| 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 | 6.91 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
532
99.5 IPS |
|
|
Image Classification (F16)
|
100% |
518
96.9 IPS |
|
|
Image Classification (I8)
|
97% |
906
169.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
644
10.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
631
10.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
771
12.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
1175
1.42 IPS |
|
|
Pose Estimation (F16)
|
100% |
1131
1.37 IPS |
|
|
Pose Estimation (I8)
|
100% |
4914
5.95 IPS |
|
|
Object Detection (F32)
|
100% |
518
38.7 IPS |
|
|
Object Detection (F16)
|
100% |
546
40.8 IPS |
|
|
Object Detection (I8)
|
61% |
1101
82.2 IPS |
|
|
Face Detection (F32)
|
100% |
1112
13.2 IPS |
|
|
Face Detection (F16)
|
100% |
1095
13.0 IPS |
|
|
Face Detection (I8)
|
86% |
1895
22.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
1144
8.87 IPS |
|
|
Depth Estimation (F16)
|
100% |
1140
8.84 IPS |
|
|
Depth Estimation (I8)
|
95% |
2115
16.4 IPS |
|
|
Style Transfer (F32)
|
100% |
1993
2.62 IPS |
|
|
Style Transfer (F16)
|
100% |
1963
2.58 IPS |
|
|
Style Transfer (I8)
|
98% |
5316
6.99 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
707
25.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
655
23.4 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2019
72.1 IPS |
|
|
Text Classification (F32)
|
100% |
610
876.6 IPS |
|
|
Text Classification (F16)
|
100% |
588
845.2 IPS |
|
|
Text Classification (I8)
|
92% |
425
611.1 IPS |
|
|
Machine Translation (F32)
|
100% |
1107
20.4 IPS |
|
|
Machine Translation (F16)
|
100% |
1078
19.8 IPS |
|
|
Machine Translation (I8)
|
64% |
501
9.22 IPS |
