Samsung Galaxy S23 Ultra
Geekbench ML Score
1026
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 22 2024 07:58 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% |
537
100.5 IPS |
|
|
Image Classification (F16)
|
100% |
521
97.4 IPS |
|
|
Image Classification (I8)
|
97% |
875
163.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
633
10.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
632
10.6 IPS |
|
|
Image Segmentation (I8)
|
98% |
807
13.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
1242
1.50 IPS |
|
|
Pose Estimation (F16)
|
100% |
1205
1.46 IPS |
|
|
Pose Estimation (I8)
|
100% |
5113
6.19 IPS |
|
|
Object Detection (F32)
|
100% |
532
39.7 IPS |
|
|
Object Detection (F16)
|
100% |
515
38.4 IPS |
|
|
Object Detection (I8)
|
61% |
968
72.3 IPS |
|
|
Face Detection (F32)
|
100% |
1063
12.6 IPS |
|
|
Face Detection (F16)
|
100% |
1093
13.0 IPS |
|
|
Face Detection (I8)
|
86% |
1935
23.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
1062
8.24 IPS |
|
|
Depth Estimation (F16)
|
100% |
1175
9.12 IPS |
|
|
Depth Estimation (I8)
|
95% |
2135
16.6 IPS |
|
|
Style Transfer (F32)
|
100% |
2062
2.71 IPS |
|
|
Style Transfer (F16)
|
100% |
2095
2.76 IPS |
|
|
Style Transfer (I8)
|
98% |
4317
5.68 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
765
27.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
799
28.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1938
69.2 IPS |
|
|
Text Classification (F32)
|
100% |
624
897.4 IPS |
|
|
Text Classification (F16)
|
100% |
625
898.1 IPS |
|
|
Text Classification (I8)
|
92% |
426
612.9 IPS |
|
|
Machine Translation (F32)
|
100% |
1203
22.1 IPS |
|
|
Machine Translation (F16)
|
100% |
1118
20.6 IPS |
|
|
Machine Translation (I8)
|
64% |
461
8.48 IPS |
