Samsung Galaxy S23 Ultra
Geekbench ML Score
1036
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 02 2024 02:07 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 | 6.89 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
486
91.0 IPS |
|
|
Image Classification (F16)
|
100% |
509
95.3 IPS |
|
|
Image Classification (I8)
|
97% |
865
161.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
665
11.1 IPS |
|
|
Image Segmentation (F16)
|
100% |
665
11.1 IPS |
|
|
Image Segmentation (I8)
|
98% |
799
13.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
1121
1.36 IPS |
|
|
Pose Estimation (F16)
|
100% |
1162
1.41 IPS |
|
|
Pose Estimation (I8)
|
100% |
4944
5.99 IPS |
|
|
Object Detection (F32)
|
100% |
538
40.2 IPS |
|
|
Object Detection (F16)
|
100% |
548
40.9 IPS |
|
|
Object Detection (I8)
|
61% |
1211
90.4 IPS |
|
|
Face Detection (F32)
|
100% |
1158
13.8 IPS |
|
|
Face Detection (F16)
|
100% |
1130
13.4 IPS |
|
|
Face Detection (I8)
|
86% |
1985
23.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
1242
9.63 IPS |
|
|
Depth Estimation (F16)
|
100% |
1197
9.28 IPS |
|
|
Depth Estimation (I8)
|
95% |
2271
17.6 IPS |
|
|
Style Transfer (F32)
|
100% |
2076
2.73 IPS |
|
|
Style Transfer (F16)
|
100% |
2061
2.71 IPS |
|
|
Style Transfer (I8)
|
98% |
4418
5.81 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
695
24.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
781
27.9 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2195
78.4 IPS |
|
|
Text Classification (F32)
|
100% |
599
860.6 IPS |
|
|
Text Classification (F16)
|
100% |
595
854.6 IPS |
|
|
Text Classification (I8)
|
92% |
454
653.1 IPS |
|
|
Machine Translation (F32)
|
100% |
1136
20.9 IPS |
|
|
Machine Translation (F16)
|
100% |
1098
20.2 IPS |
|
|
Machine Translation (I8)
|
64% |
427
7.86 IPS |
