Samsung Galaxy S23 Ultra
Geekbench ML Score
1040
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | August 19 2024 05:39 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% |
526
98.3 IPS |
|
|
Image Classification (F16)
|
100% |
510
95.4 IPS |
|
|
Image Classification (I8)
|
97% |
875
163.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
642
10.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
635
10.6 IPS |
|
|
Image Segmentation (I8)
|
98% |
786
13.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
1190
1.44 IPS |
|
|
Pose Estimation (F16)
|
100% |
1157
1.40 IPS |
|
|
Pose Estimation (I8)
|
100% |
5005
6.06 IPS |
|
|
Object Detection (F32)
|
100% |
542
40.4 IPS |
|
|
Object Detection (F16)
|
100% |
545
40.7 IPS |
|
|
Object Detection (I8)
|
61% |
1196
89.3 IPS |
|
|
Face Detection (F32)
|
100% |
1099
13.1 IPS |
|
|
Face Detection (F16)
|
100% |
1114
13.2 IPS |
|
|
Face Detection (I8)
|
86% |
1906
22.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
1165
9.03 IPS |
|
|
Depth Estimation (F16)
|
100% |
1138
8.83 IPS |
|
|
Depth Estimation (I8)
|
95% |
2205
17.1 IPS |
|
|
Style Transfer (F32)
|
100% |
2016
2.65 IPS |
|
|
Style Transfer (F16)
|
100% |
2112
2.78 IPS |
|
|
Style Transfer (I8)
|
98% |
4560
6.00 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
768
27.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
750
26.8 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2206
78.8 IPS |
|
|
Text Classification (F32)
|
100% |
621
892.8 IPS |
|
|
Text Classification (F16)
|
100% |
578
830.1 IPS |
|
|
Text Classification (I8)
|
92% |
467
670.9 IPS |
|
|
Machine Translation (F32)
|
100% |
1151
21.2 IPS |
|
|
Machine Translation (F16)
|
100% |
1116
20.5 IPS |
|
|
Machine Translation (I8)
|
64% |
502
9.23 IPS |
