Samsung Galaxy S23 Ultra
Geekbench ML Score
954
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 15 2024 12:57 PM |
| Views | 2 |
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% |
455
85.2 IPS |
|
|
Image Classification (F16)
|
100% |
478
89.4 IPS |
|
|
Image Classification (I8)
|
97% |
862
161.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
601
10.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
594
9.91 IPS |
|
|
Image Segmentation (I8)
|
98% |
713
11.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
1126
1.36 IPS |
|
|
Pose Estimation (F16)
|
100% |
1057
1.28 IPS |
|
|
Pose Estimation (I8)
|
100% |
4403
5.33 IPS |
|
|
Object Detection (F32)
|
100% |
486
36.3 IPS |
|
|
Object Detection (F16)
|
100% |
482
36.0 IPS |
|
|
Object Detection (I8)
|
61% |
1100
82.2 IPS |
|
|
Face Detection (F32)
|
100% |
1037
12.3 IPS |
|
|
Face Detection (F16)
|
100% |
1050
12.5 IPS |
|
|
Face Detection (I8)
|
86% |
1784
21.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
1037
8.04 IPS |
|
|
Depth Estimation (F16)
|
100% |
1041
8.07 IPS |
|
|
Depth Estimation (I8)
|
95% |
1965
15.2 IPS |
|
|
Style Transfer (F32)
|
100% |
1790
2.35 IPS |
|
|
Style Transfer (F16)
|
100% |
1790
2.35 IPS |
|
|
Style Transfer (I8)
|
98% |
4087
5.38 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
629
22.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
687
24.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1833
65.5 IPS |
|
|
Text Classification (F32)
|
100% |
623
895.5 IPS |
|
|
Text Classification (F16)
|
100% |
614
882.9 IPS |
|
|
Text Classification (I8)
|
92% |
466
670.2 IPS |
|
|
Machine Translation (F32)
|
100% |
1019
18.7 IPS |
|
|
Machine Translation (F16)
|
100% |
1008
18.5 IPS |
|
|
Machine Translation (I8)
|
64% |
487
8.96 IPS |
