Samsung Galaxy S23 Ultra
Geekbench ML Score
975
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 20 2024 04:56 AM |
| Views | 3 |
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% |
511
95.7 IPS |
|
|
Image Classification (F16)
|
100% |
480
89.8 IPS |
|
|
Image Classification (I8)
|
97% |
851
159.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
623
10.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
614
10.3 IPS |
|
|
Image Segmentation (I8)
|
98% |
775
12.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
1079
1.31 IPS |
|
|
Pose Estimation (F16)
|
100% |
918
1.11 IPS |
|
|
Pose Estimation (I8)
|
100% |
4442
5.38 IPS |
|
|
Object Detection (F32)
|
100% |
524
39.1 IPS |
|
|
Object Detection (F16)
|
100% |
498
37.2 IPS |
|
|
Object Detection (I8)
|
61% |
1074
80.2 IPS |
|
|
Face Detection (F32)
|
100% |
1117
13.3 IPS |
|
|
Face Detection (F16)
|
100% |
1051
12.5 IPS |
|
|
Face Detection (I8)
|
86% |
1753
20.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
1069
8.29 IPS |
|
|
Depth Estimation (F16)
|
100% |
1060
8.22 IPS |
|
|
Depth Estimation (I8)
|
95% |
2175
16.9 IPS |
|
|
Style Transfer (F32)
|
100% |
1804
2.37 IPS |
|
|
Style Transfer (F16)
|
100% |
1805
2.37 IPS |
|
|
Style Transfer (I8)
|
98% |
4275
5.62 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
709
25.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
717
25.6 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2052
73.3 IPS |
|
|
Text Classification (F32)
|
100% |
623
894.9 IPS |
|
|
Text Classification (F16)
|
100% |
631
907.2 IPS |
|
|
Text Classification (I8)
|
92% |
394
566.9 IPS |
|
|
Machine Translation (F32)
|
100% |
1084
19.9 IPS |
|
|
Machine Translation (F16)
|
100% |
1053
19.4 IPS |
|
|
Machine Translation (I8)
|
64% |
480
8.83 IPS |
