Samsung Galaxy S23
Geekbench ML Score
1004
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | March 27 2024 07:13 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% |
499
93.4 IPS |
|
|
Image Classification (F16)
|
100% |
495
92.7 IPS |
|
|
Image Classification (I8)
|
97% |
867
162.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
587
9.81 IPS |
|
|
Image Segmentation (F16)
|
100% |
586
9.78 IPS |
|
|
Image Segmentation (I8)
|
98% |
775
12.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
1110
1.34 IPS |
|
|
Pose Estimation (F16)
|
100% |
1126
1.36 IPS |
|
|
Pose Estimation (I8)
|
100% |
4721
5.72 IPS |
|
|
Object Detection (F32)
|
100% |
521
38.9 IPS |
|
|
Object Detection (F16)
|
100% |
511
38.2 IPS |
|
|
Object Detection (I8)
|
61% |
1113
83.1 IPS |
|
|
Face Detection (F32)
|
100% |
1100
13.1 IPS |
|
|
Face Detection (F16)
|
100% |
1104
13.1 IPS |
|
|
Face Detection (I8)
|
86% |
1881
22.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
1156
8.97 IPS |
|
|
Depth Estimation (F16)
|
100% |
1138
8.82 IPS |
|
|
Depth Estimation (I8)
|
95% |
2119
16.4 IPS |
|
|
Style Transfer (F32)
|
100% |
1917
2.52 IPS |
|
|
Style Transfer (F16)
|
100% |
1912
2.52 IPS |
|
|
Style Transfer (I8)
|
98% |
4438
5.84 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
753
26.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
742
26.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1841
65.7 IPS |
|
|
Text Classification (F32)
|
100% |
620
890.6 IPS |
|
|
Text Classification (F16)
|
100% |
649
932.6 IPS |
|
|
Text Classification (I8)
|
92% |
430
617.5 IPS |
|
|
Machine Translation (F32)
|
100% |
1138
20.9 IPS |
|
|
Machine Translation (F16)
|
100% |
1118
20.6 IPS |
|
|
Machine Translation (I8)
|
64% |
484
8.90 IPS |
