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 | January 21 2024 04:00 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% |
478
89.4 IPS |
|
|
Image Classification (F16)
|
100% |
435
81.5 IPS |
|
|
Image Classification (I8)
|
97% |
813
152.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
626
10.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
620
10.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
777
13.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
1199
1.45 IPS |
|
|
Pose Estimation (F16)
|
100% |
1168
1.41 IPS |
|
|
Pose Estimation (I8)
|
100% |
4900
5.93 IPS |
|
|
Object Detection (F32)
|
100% |
554
41.3 IPS |
|
|
Object Detection (F16)
|
100% |
552
41.2 IPS |
|
|
Object Detection (I8)
|
61% |
1130
84.4 IPS |
|
|
Face Detection (F32)
|
100% |
1095
13.0 IPS |
|
|
Face Detection (F16)
|
100% |
1056
12.6 IPS |
|
|
Face Detection (I8)
|
86% |
1829
21.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
1145
8.88 IPS |
|
|
Depth Estimation (F16)
|
100% |
1160
8.99 IPS |
|
|
Depth Estimation (I8)
|
95% |
2197
17.0 IPS |
|
|
Style Transfer (F32)
|
100% |
2047
2.69 IPS |
|
|
Style Transfer (F16)
|
100% |
2016
2.65 IPS |
|
|
Style Transfer (I8)
|
98% |
4133
5.44 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
727
26.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
760
27.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2065
73.8 IPS |
|
|
Text Classification (F32)
|
100% |
606
870.3 IPS |
|
|
Text Classification (F16)
|
100% |
578
830.5 IPS |
|
|
Text Classification (I8)
|
92% |
416
597.7 IPS |
|
|
Machine Translation (F32)
|
100% |
1096
20.2 IPS |
|
|
Machine Translation (F16)
|
100% |
1067
19.6 IPS |
|
|
Machine Translation (I8)
|
64% |
452
8.32 IPS |
