Samsung Galaxy S23 Ultra
Geekbench ML Score
1027
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | February 23 2024 01:10 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S23 Ultra |
| Model ID | samsung SM-S918U1 |
| 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% |
514
96.1 IPS |
|
|
Image Classification (F16)
|
100% |
514
96.2 IPS |
|
|
Image Classification (I8)
|
97% |
861
161.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
640
10.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
618
10.3 IPS |
|
|
Image Segmentation (I8)
|
98% |
771
12.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
1196
1.45 IPS |
|
|
Pose Estimation (F16)
|
100% |
1148
1.39 IPS |
|
|
Pose Estimation (I8)
|
100% |
4997
6.05 IPS |
|
|
Object Detection (F32)
|
100% |
544
40.6 IPS |
|
|
Object Detection (F16)
|
100% |
535
39.9 IPS |
|
|
Object Detection (I8)
|
61% |
1159
86.5 IPS |
|
|
Face Detection (F32)
|
100% |
1123
13.4 IPS |
|
|
Face Detection (F16)
|
100% |
1110
13.2 IPS |
|
|
Face Detection (I8)
|
86% |
1899
22.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
1135
8.80 IPS |
|
|
Depth Estimation (F16)
|
100% |
1132
8.78 IPS |
|
|
Depth Estimation (I8)
|
95% |
2189
17.0 IPS |
|
|
Style Transfer (F32)
|
100% |
2102
2.77 IPS |
|
|
Style Transfer (F16)
|
100% |
2033
2.67 IPS |
|
|
Style Transfer (I8)
|
98% |
4384
5.77 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
772
27.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
752
26.9 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1980
70.7 IPS |
|
|
Text Classification (F32)
|
100% |
572
822.7 IPS |
|
|
Text Classification (F16)
|
100% |
628
903.2 IPS |
|
|
Text Classification (I8)
|
92% |
452
650.0 IPS |
|
|
Machine Translation (F32)
|
100% |
1152
21.2 IPS |
|
|
Machine Translation (F16)
|
100% |
1066
19.6 IPS |
|
|
Machine Translation (I8)
|
64% |
492
9.06 IPS |
