Samsung Galaxy S23 Ultra
Geekbench ML Score
1015
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | November 15 2024 02:03 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% |
510
95.4 IPS |
|
|
Image Classification (F16)
|
100% |
498
93.2 IPS |
|
|
Image Classification (I8)
|
97% |
851
159.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
632
10.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
642
10.7 IPS |
|
|
Image Segmentation (I8)
|
98% |
803
13.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
1022
1.24 IPS |
|
|
Pose Estimation (F16)
|
100% |
1112
1.35 IPS |
|
|
Pose Estimation (I8)
|
100% |
5171
6.26 IPS |
|
|
Object Detection (F32)
|
100% |
522
38.9 IPS |
|
|
Object Detection (F16)
|
100% |
512
38.2 IPS |
|
|
Object Detection (I8)
|
61% |
1088
81.2 IPS |
|
|
Face Detection (F32)
|
100% |
1110
13.2 IPS |
|
|
Face Detection (F16)
|
100% |
1080
12.8 IPS |
|
|
Face Detection (I8)
|
86% |
1881
22.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
1126
8.73 IPS |
|
|
Depth Estimation (F16)
|
100% |
1116
8.66 IPS |
|
|
Depth Estimation (I8)
|
95% |
2199
17.1 IPS |
|
|
Style Transfer (F32)
|
100% |
1932
2.54 IPS |
|
|
Style Transfer (F16)
|
100% |
1965
2.58 IPS |
|
|
Style Transfer (I8)
|
98% |
4447
5.85 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
769
27.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
741
26.4 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2082
74.3 IPS |
|
|
Text Classification (F32)
|
100% |
607
871.8 IPS |
|
|
Text Classification (F16)
|
100% |
625
898.7 IPS |
|
|
Text Classification (I8)
|
92% |
471
677.0 IPS |
|
|
Machine Translation (F32)
|
100% |
1107
20.4 IPS |
|
|
Machine Translation (F16)
|
100% |
1086
20.0 IPS |
|
|
Machine Translation (I8)
|
64% |
488
8.99 IPS |
