Samsung Galaxy S23 Ultra
Geekbench ML Score
1046
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 21 2024 04:19 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% |
524
98.1 IPS |
|
|
Image Classification (F16)
|
100% |
509
95.3 IPS |
|
|
Image Classification (I8)
|
97% |
891
166.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
653
10.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
659
11.0 IPS |
|
|
Image Segmentation (I8)
|
98% |
786
13.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
1221
1.48 IPS |
|
|
Pose Estimation (F16)
|
100% |
1219
1.48 IPS |
|
|
Pose Estimation (I8)
|
100% |
5177
6.27 IPS |
|
|
Object Detection (F32)
|
100% |
540
40.3 IPS |
|
|
Object Detection (F16)
|
100% |
552
41.2 IPS |
|
|
Object Detection (I8)
|
61% |
1208
90.2 IPS |
|
|
Face Detection (F32)
|
100% |
1096
13.0 IPS |
|
|
Face Detection (F16)
|
100% |
1116
13.3 IPS |
|
|
Face Detection (I8)
|
86% |
1876
22.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
1168
9.06 IPS |
|
|
Depth Estimation (F16)
|
100% |
1177
9.12 IPS |
|
|
Depth Estimation (I8)
|
95% |
2177
16.9 IPS |
|
|
Style Transfer (F32)
|
100% |
2110
2.78 IPS |
|
|
Style Transfer (F16)
|
100% |
2129
2.80 IPS |
|
|
Style Transfer (I8)
|
98% |
4270
5.62 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
781
27.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
804
28.7 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1975
70.5 IPS |
|
|
Text Classification (F32)
|
100% |
612
880.1 IPS |
|
|
Text Classification (F16)
|
100% |
631
907.4 IPS |
|
|
Text Classification (I8)
|
92% |
439
631.1 IPS |
|
|
Machine Translation (F32)
|
100% |
1229
22.6 IPS |
|
|
Machine Translation (F16)
|
100% |
1185
21.8 IPS |
|
|
Machine Translation (I8)
|
64% |
431
7.92 IPS |
