Samsung Galaxy S23
Geekbench ML Score
570
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 18 2024 02:50 PM |
| Views | 2 |
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 | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
283
53.0 IPS |
|
|
Image Classification (F16)
|
100% |
268
50.2 IPS |
|
|
Image Classification (I8)
|
97% |
681
127.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
331
5.52 IPS |
|
|
Image Segmentation (F16)
|
100% |
326
5.44 IPS |
|
|
Image Segmentation (I8)
|
98% |
695
11.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
454
0.55 IPS |
|
|
Pose Estimation (F16)
|
100% |
449
0.54 IPS |
|
|
Pose Estimation (I8)
|
100% |
1872
2.27 IPS |
|
|
Object Detection (F32)
|
100% |
286
21.3 IPS |
|
|
Object Detection (F16)
|
100% |
292
21.8 IPS |
|
|
Object Detection (I8)
|
61% |
824
61.5 IPS |
|
|
Face Detection (F32)
|
100% |
659
7.83 IPS |
|
|
Face Detection (F16)
|
100% |
648
7.71 IPS |
|
|
Face Detection (I8)
|
86% |
1476
17.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
570
4.42 IPS |
|
|
Depth Estimation (F16)
|
100% |
567
4.39 IPS |
|
|
Depth Estimation (I8)
|
95% |
1659
12.9 IPS |
|
|
Style Transfer (F32)
|
100% |
913
1.20 IPS |
|
|
Style Transfer (F16)
|
100% |
895
1.18 IPS |
|
|
Style Transfer (I8)
|
98% |
2065
2.72 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
301
10.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
301
10.7 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
997
35.6 IPS |
|
|
Text Classification (F32)
|
100% |
328
471.9 IPS |
|
|
Text Classification (F16)
|
100% |
328
471.3 IPS |
|
|
Text Classification (I8)
|
92% |
475
682.0 IPS |
|
|
Machine Translation (F32)
|
100% |
583
10.7 IPS |
|
|
Machine Translation (F16)
|
100% |
560
10.3 IPS |
|
|
Machine Translation (I8)
|
64% |
548
10.1 IPS |
