Samsung Galaxy S23 Ultra
Geekbench ML Score
1010
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 20 2024 05:25 AM |
| Views | 4 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S23 Ultra |
| Model ID | samsung SM-S9180 |
| 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% |
461
86.2 IPS |
|
|
Image Classification (F16)
|
100% |
492
92.0 IPS |
|
|
Image Classification (I8)
|
97% |
860
161.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
639
10.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
622
10.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
767
12.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
1139
1.38 IPS |
|
|
Pose Estimation (F16)
|
100% |
1083
1.31 IPS |
|
|
Pose Estimation (I8)
|
100% |
4752
5.75 IPS |
|
|
Object Detection (F32)
|
100% |
548
40.9 IPS |
|
|
Object Detection (F16)
|
100% |
555
41.4 IPS |
|
|
Object Detection (I8)
|
61% |
1199
89.5 IPS |
|
|
Face Detection (F32)
|
100% |
1113
13.2 IPS |
|
|
Face Detection (F16)
|
100% |
1078
12.8 IPS |
|
|
Face Detection (I8)
|
86% |
1826
21.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
1082
8.39 IPS |
|
|
Depth Estimation (F16)
|
100% |
1131
8.77 IPS |
|
|
Depth Estimation (I8)
|
95% |
2150
16.7 IPS |
|
|
Style Transfer (F32)
|
100% |
1907
2.51 IPS |
|
|
Style Transfer (F16)
|
100% |
2040
2.68 IPS |
|
|
Style Transfer (I8)
|
98% |
4157
5.47 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
742
26.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
716
25.6 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1936
69.1 IPS |
|
|
Text Classification (F32)
|
100% |
612
879.4 IPS |
|
|
Text Classification (F16)
|
100% |
630
905.0 IPS |
|
|
Text Classification (I8)
|
92% |
463
664.9 IPS |
|
|
Machine Translation (F32)
|
100% |
1182
21.8 IPS |
|
|
Machine Translation (F16)
|
100% |
1065
19.6 IPS |
|
|
Machine Translation (I8)
|
64% |
502
9.23 IPS |
