Samsung Galaxy S23
Geekbench ML Score
1120
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| User | korbs |
| Upload Date | July 25 2024 09:20 PM |
| Views | 4 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S23 |
| Model ID | samsung SM-S911U |
| 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
653
122.3 IPS |
|
|
Image Classification (F16)
|
100% |
930
174.0 IPS |
|
|
Image Classification (I8)
|
99% |
811
151.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
1056
17.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
1215
20.3 IPS |
|
|
Image Segmentation (I8)
|
98% |
1345
22.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
971
1.18 IPS |
|
|
Pose Estimation (F16)
|
100% |
1395
1.69 IPS |
|
|
Pose Estimation (I8)
|
100% |
1384
1.68 IPS |
|
|
Object Detection (F32)
|
100% |
360
26.9 IPS |
|
|
Object Detection (F16)
|
100% |
486
36.3 IPS |
|
|
Object Detection (I8)
|
62% |
496
37.0 IPS |
|
|
Face Detection (F32)
|
100% |
2305
27.4 IPS |
|
|
Face Detection (F16)
|
97% |
3671
43.7 IPS |
|
|
Face Detection (I8)
|
86% |
3084
36.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
1516
11.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
2953
22.9 IPS |
|
|
Depth Estimation (I8)
|
95% |
2926
22.7 IPS |
|
|
Style Transfer (F32)
|
100% |
3804
5.00 IPS |
|
|
Style Transfer (F16)
|
100% |
8592
11.3 IPS |
|
|
Style Transfer (I8)
|
98% |
8567
11.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
482
17.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
386
13.8 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
393
14.0 IPS |
|
|
Text Classification (F32)
|
100% |
421
605.4 IPS |
|
|
Text Classification (F16)
|
100% |
421
605.0 IPS |
|
|
Text Classification (I8)
|
92% |
601
863.6 IPS |
|
|
Machine Translation (F32)
|
100% |
675
12.4 IPS |
|
|
Machine Translation (F16)
|
100% |
632
11.6 IPS |
|
|
Machine Translation (I8)
|
64% |
695
12.8 IPS |
