Samsung Galaxy S23 Ultra
Geekbench ML Score
981
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 01 2024 07:42 AM |
| 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% |
464
86.9 IPS |
|
|
Image Classification (F16)
|
100% |
446
83.5 IPS |
|
|
Image Classification (I8)
|
97% |
832
155.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
583
9.74 IPS |
|
|
Image Segmentation (F16)
|
100% |
589
9.84 IPS |
|
|
Image Segmentation (I8)
|
98% |
765
12.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
1078
1.30 IPS |
|
|
Pose Estimation (F16)
|
100% |
1081
1.31 IPS |
|
|
Pose Estimation (I8)
|
100% |
4583
5.55 IPS |
|
|
Object Detection (F32)
|
100% |
490
36.6 IPS |
|
|
Object Detection (F16)
|
100% |
510
38.1 IPS |
|
|
Object Detection (I8)
|
61% |
1165
87.0 IPS |
|
|
Face Detection (F32)
|
100% |
1102
13.1 IPS |
|
|
Face Detection (F16)
|
100% |
1094
13.0 IPS |
|
|
Face Detection (I8)
|
86% |
1803
21.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
1114
8.64 IPS |
|
|
Depth Estimation (F16)
|
100% |
1093
8.48 IPS |
|
|
Depth Estimation (I8)
|
95% |
2108
16.3 IPS |
|
|
Style Transfer (F32)
|
100% |
1940
2.55 IPS |
|
|
Style Transfer (F16)
|
100% |
1899
2.50 IPS |
|
|
Style Transfer (I8)
|
98% |
4125
5.43 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
733
26.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
731
26.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1882
67.2 IPS |
|
|
Text Classification (F32)
|
100% |
620
891.2 IPS |
|
|
Text Classification (F16)
|
100% |
594
853.6 IPS |
|
|
Text Classification (I8)
|
92% |
446
640.5 IPS |
|
|
Machine Translation (F32)
|
100% |
1109
20.4 IPS |
|
|
Machine Translation (F16)
|
100% |
1052
19.4 IPS |
|
|
Machine Translation (I8)
|
64% |
493
9.08 IPS |
