Samsung Galaxy S23 Ultra
Geekbench ML Score
924
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | November 26 2024 03:38 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S23 Ultra |
| Model ID | samsung SM-S918B |
| 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 | 10.77 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
416
77.8 IPS |
|
|
Image Classification (F16)
|
100% |
439
82.2 IPS |
|
|
Image Classification (I8)
|
97% |
769
143.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
593
9.91 IPS |
|
|
Image Segmentation (F16)
|
100% |
583
9.74 IPS |
|
|
Image Segmentation (I8)
|
98% |
767
12.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
1098
1.33 IPS |
|
|
Pose Estimation (F16)
|
100% |
1104
1.34 IPS |
|
|
Pose Estimation (I8)
|
100% |
4518
5.47 IPS |
|
|
Object Detection (F32)
|
100% |
484
36.2 IPS |
|
|
Object Detection (F16)
|
100% |
472
35.2 IPS |
|
|
Object Detection (I8)
|
61% |
984
73.4 IPS |
|
|
Face Detection (F32)
|
100% |
1002
11.9 IPS |
|
|
Face Detection (F16)
|
100% |
1029
12.2 IPS |
|
|
Face Detection (I8)
|
86% |
1725
20.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
967
7.50 IPS |
|
|
Depth Estimation (F16)
|
100% |
1025
7.95 IPS |
|
|
Depth Estimation (I8)
|
95% |
1926
14.9 IPS |
|
|
Style Transfer (F32)
|
100% |
1859
2.44 IPS |
|
|
Style Transfer (F16)
|
100% |
1876
2.47 IPS |
|
|
Style Transfer (I8)
|
98% |
4284
5.64 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
658
23.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
664
23.7 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1820
65.0 IPS |
|
|
Text Classification (F32)
|
100% |
536
769.7 IPS |
|
|
Text Classification (F16)
|
100% |
542
778.7 IPS |
|
|
Text Classification (I8)
|
92% |
416
598.0 IPS |
|
|
Machine Translation (F32)
|
100% |
967
17.8 IPS |
|
|
Machine Translation (F16)
|
100% |
895
16.5 IPS |
|
|
Machine Translation (I8)
|
64% |
483
8.89 IPS |
