Samsung Galaxy S23 Ultra
Geekbench ML Score
1003
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 08 2024 03:28 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% |
509
95.2 IPS |
|
|
Image Classification (F16)
|
100% |
501
93.7 IPS |
|
|
Image Classification (I8)
|
97% |
815
152.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
621
10.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
634
10.6 IPS |
|
|
Image Segmentation (I8)
|
98% |
783
13.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
1210
1.47 IPS |
|
|
Pose Estimation (F16)
|
100% |
1139
1.38 IPS |
|
|
Pose Estimation (I8)
|
100% |
4553
5.51 IPS |
|
|
Object Detection (F32)
|
100% |
498
37.2 IPS |
|
|
Object Detection (F16)
|
100% |
517
38.6 IPS |
|
|
Object Detection (I8)
|
61% |
1050
78.4 IPS |
|
|
Face Detection (F32)
|
100% |
1089
12.9 IPS |
|
|
Face Detection (F16)
|
100% |
1064
12.7 IPS |
|
|
Face Detection (I8)
|
86% |
1901
22.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
1154
8.95 IPS |
|
|
Depth Estimation (F16)
|
100% |
1094
8.48 IPS |
|
|
Depth Estimation (I8)
|
95% |
2114
16.4 IPS |
|
|
Style Transfer (F32)
|
100% |
1995
2.62 IPS |
|
|
Style Transfer (F16)
|
100% |
1929
2.54 IPS |
|
|
Style Transfer (I8)
|
98% |
4199
5.52 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
716
25.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
770
27.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2075
74.1 IPS |
|
|
Text Classification (F32)
|
100% |
613
880.4 IPS |
|
|
Text Classification (F16)
|
100% |
628
902.7 IPS |
|
|
Text Classification (I8)
|
92% |
425
611.0 IPS |
|
|
Machine Translation (F32)
|
100% |
1124
20.7 IPS |
|
|
Machine Translation (F16)
|
100% |
1043
19.2 IPS |
|
|
Machine Translation (I8)
|
64% |
488
8.98 IPS |
