Samsung Galaxy S23 Ultra
Geekbench ML Score
1051
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 09 2024 11:57 PM |
| Views | 4 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Samsung Galaxy S23 Ultra |
| Model ID | samsung SM-S918N |
| 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 | 10.78 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
521
97.5 IPS |
|
|
Image Classification (F16)
|
100% |
522
97.7 IPS |
|
|
Image Classification (I8)
|
97% |
824
154.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
667
11.1 IPS |
|
|
Image Segmentation (F16)
|
100% |
638
10.6 IPS |
|
|
Image Segmentation (I8)
|
98% |
755
12.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
1224
1.48 IPS |
|
|
Pose Estimation (F16)
|
100% |
1156
1.40 IPS |
|
|
Pose Estimation (I8)
|
100% |
5158
6.25 IPS |
|
|
Object Detection (F32)
|
100% |
543
40.6 IPS |
|
|
Object Detection (F16)
|
100% |
554
41.4 IPS |
|
|
Object Detection (I8)
|
61% |
1196
89.3 IPS |
|
|
Face Detection (F32)
|
100% |
1154
13.7 IPS |
|
|
Face Detection (F16)
|
100% |
1161
13.8 IPS |
|
|
Face Detection (I8)
|
86% |
2014
24.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
1189
9.22 IPS |
|
|
Depth Estimation (F16)
|
100% |
1149
8.91 IPS |
|
|
Depth Estimation (I8)
|
95% |
2260
17.5 IPS |
|
|
Style Transfer (F32)
|
100% |
2071
2.72 IPS |
|
|
Style Transfer (F16)
|
100% |
2091
2.75 IPS |
|
|
Style Transfer (I8)
|
98% |
5392
7.09 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
742
26.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
809
28.9 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2088
74.6 IPS |
|
|
Text Classification (F32)
|
100% |
621
892.5 IPS |
|
|
Text Classification (F16)
|
100% |
613
880.3 IPS |
|
|
Text Classification (I8)
|
92% |
430
617.5 IPS |
|
|
Machine Translation (F32)
|
100% |
1172
21.6 IPS |
|
|
Machine Translation (F16)
|
100% |
1180
21.7 IPS |
|
|
Machine Translation (I8)
|
64% |
432
7.94 IPS |
