Samsung Galaxy S23 Ultra
Geekbench ML Score
579
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 22 2024 02:27 PM |
| Views | 3 |
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% |
468
87.6 IPS |
|
|
Image Classification (F16)
|
100% |
463
86.7 IPS |
|
|
Image Classification (I8)
|
97% |
851
159.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
594
9.92 IPS |
|
|
Image Segmentation (F16)
|
100% |
599
10.0 IPS |
|
|
Image Segmentation (I8)
|
98% |
746
12.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
953
1.15 IPS |
|
|
Pose Estimation (F16)
|
100% |
1050
1.27 IPS |
|
|
Pose Estimation (I8)
|
100% |
4456
5.40 IPS |
|
|
Object Detection (F32)
|
100% |
485
36.2 IPS |
|
|
Object Detection (F16)
|
100% |
489
36.5 IPS |
|
|
Object Detection (I8)
|
61% |
1131
84.4 IPS |
|
|
Face Detection (F32)
|
100% |
1067
12.7 IPS |
|
|
Face Detection (F16)
|
100% |
1068
12.7 IPS |
|
|
Face Detection (I8)
|
86% |
1723
20.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
1042
8.08 IPS |
|
|
Depth Estimation (F16)
|
100% |
1001
7.77 IPS |
|
|
Depth Estimation (I8)
|
95% |
1992
15.4 IPS |
|
|
Style Transfer (F32)
|
100% |
1811
2.38 IPS |
|
|
Style Transfer (F16)
|
100% |
1771
2.33 IPS |
|
|
Style Transfer (I8)
|
98% |
3639
4.79 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
252
9.01 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
263
9.40 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
543
19.4 IPS |
|
|
Text Classification (F32)
|
100% |
29
41.2 IPS |
|
|
Text Classification (F16)
|
100% |
58
83.4 IPS |
|
|
Text Classification (I8)
|
92% |
25
35.3 IPS |
|
|
Machine Translation (F32)
|
100% |
42
0.78 IPS |
|
|
Machine Translation (F16)
|
100% |
1037
19.1 IPS |
|
|
Machine Translation (I8)
|
64% |
434
7.98 IPS |
