Samsung Galaxy S23
Geekbench ML Score
962
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 18 2024 04:07 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S23 |
| Model ID | samsung SM-S911B |
| 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% |
520
97.3 IPS |
|
|
Image Classification (F16)
|
100% |
509
95.3 IPS |
|
|
Image Classification (I8)
|
97% |
800
149.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
602
10.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
607
10.1 IPS |
|
|
Image Segmentation (I8)
|
98% |
733
12.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
1099
1.33 IPS |
|
|
Pose Estimation (F16)
|
100% |
1094
1.33 IPS |
|
|
Pose Estimation (I8)
|
100% |
4455
5.39 IPS |
|
|
Object Detection (F32)
|
100% |
501
37.4 IPS |
|
|
Object Detection (F16)
|
100% |
510
38.1 IPS |
|
|
Object Detection (I8)
|
61% |
1150
85.8 IPS |
|
|
Face Detection (F32)
|
100% |
1105
13.1 IPS |
|
|
Face Detection (F16)
|
100% |
1105
13.1 IPS |
|
|
Face Detection (I8)
|
86% |
1678
20.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
1048
8.13 IPS |
|
|
Depth Estimation (F16)
|
100% |
1059
8.22 IPS |
|
|
Depth Estimation (I8)
|
95% |
1881
14.6 IPS |
|
|
Style Transfer (F32)
|
100% |
1795
2.36 IPS |
|
|
Style Transfer (F16)
|
100% |
1850
2.43 IPS |
|
|
Style Transfer (I8)
|
98% |
3898
5.13 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
684
24.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
649
23.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2011
71.8 IPS |
|
|
Text Classification (F32)
|
100% |
614
881.8 IPS |
|
|
Text Classification (F16)
|
100% |
501
720.6 IPS |
|
|
Text Classification (I8)
|
92% |
445
639.8 IPS |
|
|
Machine Translation (F32)
|
100% |
1066
19.6 IPS |
|
|
Machine Translation (F16)
|
100% |
986
18.2 IPS |
|
|
Machine Translation (I8)
|
64% |
495
9.11 IPS |
