Samsung Galaxy S23 Ultra
Geekbench ML Score
1030
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | August 24 2024 02:59 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| 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 | 10.80 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
530
99.1 IPS |
|
|
Image Classification (F16)
|
100% |
520
97.4 IPS |
|
|
Image Classification (I8)
|
97% |
853
159.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
645
10.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
657
11.0 IPS |
|
|
Image Segmentation (I8)
|
98% |
814
13.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
1249
1.51 IPS |
|
|
Pose Estimation (F16)
|
100% |
1193
1.44 IPS |
|
|
Pose Estimation (I8)
|
100% |
5130
6.21 IPS |
|
|
Object Detection (F32)
|
100% |
552
41.2 IPS |
|
|
Object Detection (F16)
|
100% |
537
40.1 IPS |
|
|
Object Detection (I8)
|
61% |
1203
89.8 IPS |
|
|
Face Detection (F32)
|
100% |
1110
13.2 IPS |
|
|
Face Detection (F16)
|
100% |
1090
13.0 IPS |
|
|
Face Detection (I8)
|
86% |
1942
23.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
1119
8.68 IPS |
|
|
Depth Estimation (F16)
|
100% |
1132
8.78 IPS |
|
|
Depth Estimation (I8)
|
95% |
2172
16.8 IPS |
|
|
Style Transfer (F32)
|
100% |
2012
2.65 IPS |
|
|
Style Transfer (F16)
|
100% |
2035
2.68 IPS |
|
|
Style Transfer (I8)
|
98% |
5118
6.73 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
685
24.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
708
25.3 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2158
77.1 IPS |
|
|
Text Classification (F32)
|
100% |
599
860.4 IPS |
|
|
Text Classification (F16)
|
100% |
575
826.5 IPS |
|
|
Text Classification (I8)
|
92% |
434
624.3 IPS |
|
|
Machine Translation (F32)
|
100% |
1087
20.0 IPS |
|
|
Machine Translation (F16)
|
100% |
1075
19.8 IPS |
|
|
Machine Translation (I8)
|
64% |
445
8.19 IPS |
