Samsung Galaxy S23 Ultra
Geekbench ML Score
964
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 25 2024 08:43 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% |
480
89.9 IPS |
|
|
Image Classification (F16)
|
100% |
476
89.0 IPS |
|
|
Image Classification (I8)
|
97% |
787
147.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
600
10.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
613
10.2 IPS |
|
|
Image Segmentation (I8)
|
98% |
743
12.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
1005
1.22 IPS |
|
|
Pose Estimation (F16)
|
100% |
1017
1.23 IPS |
|
|
Pose Estimation (I8)
|
100% |
4309
5.22 IPS |
|
|
Object Detection (F32)
|
100% |
500
37.3 IPS |
|
|
Object Detection (F16)
|
100% |
524
39.2 IPS |
|
|
Object Detection (I8)
|
61% |
1103
82.4 IPS |
|
|
Face Detection (F32)
|
100% |
1071
12.7 IPS |
|
|
Face Detection (F16)
|
100% |
1092
13.0 IPS |
|
|
Face Detection (I8)
|
86% |
1768
21.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
1087
8.43 IPS |
|
|
Depth Estimation (F16)
|
100% |
1054
8.17 IPS |
|
|
Depth Estimation (I8)
|
95% |
2046
15.9 IPS |
|
|
Style Transfer (F32)
|
100% |
1806
2.38 IPS |
|
|
Style Transfer (F16)
|
100% |
1928
2.54 IPS |
|
|
Style Transfer (I8)
|
98% |
3863
5.08 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
681
24.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
691
24.7 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1806
64.5 IPS |
|
|
Text Classification (F32)
|
100% |
625
897.5 IPS |
|
|
Text Classification (F16)
|
100% |
602
865.6 IPS |
|
|
Text Classification (I8)
|
92% |
463
665.6 IPS |
|
|
Machine Translation (F32)
|
100% |
1150
21.2 IPS |
|
|
Machine Translation (F16)
|
100% |
1033
19.0 IPS |
|
|
Machine Translation (I8)
|
64% |
476
8.76 IPS |
