Samsung Galaxy S23 Ultra
Geekbench ML Score
1014
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | December 23 2024 10:47 AM |
| Views | 3 |
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 | 6.89 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
492
92.1 IPS |
|
|
Image Classification (F16)
|
100% |
488
91.3 IPS |
|
|
Image Classification (I8)
|
97% |
833
155.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
644
10.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
582
9.71 IPS |
|
|
Image Segmentation (I8)
|
98% |
773
12.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
1093
1.32 IPS |
|
|
Pose Estimation (F16)
|
100% |
1108
1.34 IPS |
|
|
Pose Estimation (I8)
|
100% |
4785
5.79 IPS |
|
|
Object Detection (F32)
|
100% |
531
39.6 IPS |
|
|
Object Detection (F16)
|
100% |
553
41.3 IPS |
|
|
Object Detection (I8)
|
61% |
1168
87.2 IPS |
|
|
Face Detection (F32)
|
100% |
1089
13.0 IPS |
|
|
Face Detection (F16)
|
100% |
1123
13.3 IPS |
|
|
Face Detection (I8)
|
86% |
1898
22.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
826
6.40 IPS |
|
|
Depth Estimation (F16)
|
100% |
977
7.58 IPS |
|
|
Depth Estimation (I8)
|
95% |
2232
17.3 IPS |
|
|
Style Transfer (F32)
|
100% |
1907
2.51 IPS |
|
|
Style Transfer (F16)
|
100% |
1545
2.03 IPS |
|
|
Style Transfer (I8)
|
98% |
4285
5.64 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
769
27.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
734
26.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2420
86.4 IPS |
|
|
Text Classification (F32)
|
100% |
699
1.00 KIPS |
|
|
Text Classification (F16)
|
100% |
690
991.8 IPS |
|
|
Text Classification (I8)
|
92% |
532
764.0 IPS |
|
|
Machine Translation (F32)
|
100% |
1240
22.8 IPS |
|
|
Machine Translation (F16)
|
100% |
1204
22.2 IPS |
|
|
Machine Translation (I8)
|
64% |
488
8.98 IPS |
