Samsung Galaxy S23
Geekbench ML Score
1065
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | March 27 2024 07:06 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
630
117.8 IPS |
|
|
Image Classification (F16)
|
100% |
505
94.6 IPS |
|
|
Image Classification (I8)
|
99% |
782
146.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
927
15.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
1048
17.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
980
16.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
906
1.10 IPS |
|
|
Pose Estimation (F16)
|
100% |
1314
1.59 IPS |
|
|
Pose Estimation (I8)
|
100% |
1295
1.57 IPS |
|
|
Object Detection (F32)
|
100% |
473
35.3 IPS |
|
|
Object Detection (F16)
|
100% |
511
38.1 IPS |
|
|
Object Detection (I8)
|
62% |
527
39.4 IPS |
|
|
Face Detection (F32)
|
100% |
2240
26.6 IPS |
|
|
Face Detection (F16)
|
97% |
3483
41.4 IPS |
|
|
Face Detection (I8)
|
86% |
3321
39.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
1456
11.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
2792
21.6 IPS |
|
|
Depth Estimation (I8)
|
95% |
2794
21.7 IPS |
|
|
Style Transfer (F32)
|
100% |
3779
4.97 IPS |
|
|
Style Transfer (F16)
|
100% |
8494
11.2 IPS |
|
|
Style Transfer (I8)
|
98% |
8402
11.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
433
15.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
379
13.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
370
13.2 IPS |
|
|
Text Classification (F32)
|
100% |
417
599.4 IPS |
|
|
Text Classification (F16)
|
100% |
421
605.1 IPS |
|
|
Text Classification (I8)
|
92% |
600
862.9 IPS |
|
|
Machine Translation (F32)
|
100% |
633
11.6 IPS |
|
|
Machine Translation (F16)
|
100% |
647
11.9 IPS |
|
|
Machine Translation (I8)
|
64% |
698
12.8 IPS |
