Samsung Galaxy S23
Geekbench ML Score
1055
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 08 2024 03:13 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S23 |
| Model ID | samsung SM-S9110 |
| 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 | 6.89 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
414
77.5 IPS |
|
|
Image Classification (F16)
|
100% |
502
94.0 IPS |
|
|
Image Classification (I8)
|
97% |
895
167.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
609
10.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
606
10.1 IPS |
|
|
Image Segmentation (I8)
|
98% |
767
12.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
1085
1.31 IPS |
|
|
Pose Estimation (F16)
|
100% |
1142
1.38 IPS |
|
|
Pose Estimation (I8)
|
100% |
4986
6.04 IPS |
|
|
Object Detection (F32)
|
100% |
566
42.2 IPS |
|
|
Object Detection (F16)
|
100% |
524
39.1 IPS |
|
|
Object Detection (I8)
|
61% |
1262
94.2 IPS |
|
|
Face Detection (F32)
|
100% |
1092
13.0 IPS |
|
|
Face Detection (F16)
|
100% |
1140
13.5 IPS |
|
|
Face Detection (I8)
|
86% |
2086
24.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
1124
8.72 IPS |
|
|
Depth Estimation (F16)
|
100% |
1122
8.70 IPS |
|
|
Depth Estimation (I8)
|
95% |
2297
17.8 IPS |
|
|
Style Transfer (F32)
|
100% |
1917
2.52 IPS |
|
|
Style Transfer (F16)
|
100% |
1909
2.51 IPS |
|
|
Style Transfer (I8)
|
98% |
4135
5.44 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
769
27.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
760
27.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2389
85.3 IPS |
|
|
Text Classification (F32)
|
100% |
727
1.04 KIPS |
|
|
Text Classification (F16)
|
100% |
749
1.08 KIPS |
|
|
Text Classification (I8)
|
92% |
668
960.6 IPS |
|
|
Machine Translation (F32)
|
100% |
1279
23.5 IPS |
|
|
Machine Translation (F16)
|
100% |
1157
21.3 IPS |
|
|
Machine Translation (I8)
|
64% |
479
8.82 IPS |
