Samsung Galaxy S23 Ultra
Geekbench ML Score
1041
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | November 14 2024 10:06 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% |
496
92.9 IPS |
|
|
Image Classification (F16)
|
100% |
507
94.8 IPS |
|
|
Image Classification (I8)
|
97% |
851
159.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
671
11.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
659
11.0 IPS |
|
|
Image Segmentation (I8)
|
98% |
785
13.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
1230
1.49 IPS |
|
|
Pose Estimation (F16)
|
100% |
1170
1.42 IPS |
|
|
Pose Estimation (I8)
|
100% |
4786
5.80 IPS |
|
|
Object Detection (F32)
|
100% |
534
39.8 IPS |
|
|
Object Detection (F16)
|
100% |
545
40.7 IPS |
|
|
Object Detection (I8)
|
61% |
1123
83.9 IPS |
|
|
Face Detection (F32)
|
100% |
1134
13.5 IPS |
|
|
Face Detection (F16)
|
100% |
1141
13.6 IPS |
|
|
Face Detection (I8)
|
86% |
2032
24.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
1210
9.38 IPS |
|
|
Depth Estimation (F16)
|
100% |
1186
9.20 IPS |
|
|
Depth Estimation (I8)
|
95% |
2220
17.2 IPS |
|
|
Style Transfer (F32)
|
100% |
2052
2.70 IPS |
|
|
Style Transfer (F16)
|
100% |
2078
2.73 IPS |
|
|
Style Transfer (I8)
|
98% |
4203
5.53 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
767
27.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
805
28.8 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2261
80.7 IPS |
|
|
Text Classification (F32)
|
100% |
596
856.8 IPS |
|
|
Text Classification (F16)
|
100% |
615
884.1 IPS |
|
|
Text Classification (I8)
|
92% |
445
639.2 IPS |
|
|
Machine Translation (F32)
|
100% |
1194
22.0 IPS |
|
|
Machine Translation (F16)
|
100% |
1136
20.9 IPS |
|
|
Machine Translation (I8)
|
64% |
439
8.08 IPS |
