Samsung Galaxy S23 Ultra
Geekbench ML Score
636
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 22 2024 08:38 PM |
| 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 | 10.77 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
298
55.7 IPS |
|
|
Image Classification (F16)
|
100% |
291
54.5 IPS |
|
|
Image Classification (I8)
|
97% |
733
137.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
357
5.96 IPS |
|
|
Image Segmentation (F16)
|
100% |
354
5.91 IPS |
|
|
Image Segmentation (I8)
|
98% |
729
12.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
487
0.59 IPS |
|
|
Pose Estimation (F16)
|
100% |
483
0.59 IPS |
|
|
Pose Estimation (I8)
|
100% |
1987
2.41 IPS |
|
|
Object Detection (F32)
|
100% |
303
22.6 IPS |
|
|
Object Detection (F16)
|
100% |
300
22.4 IPS |
|
|
Object Detection (I8)
|
61% |
837
62.5 IPS |
|
|
Face Detection (F32)
|
100% |
686
8.15 IPS |
|
|
Face Detection (F16)
|
100% |
685
8.15 IPS |
|
|
Face Detection (I8)
|
86% |
1573
18.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
604
4.68 IPS |
|
|
Depth Estimation (F16)
|
100% |
601
4.66 IPS |
|
|
Depth Estimation (I8)
|
95% |
1757
13.6 IPS |
|
|
Style Transfer (F32)
|
100% |
978
1.29 IPS |
|
|
Style Transfer (F16)
|
100% |
972
1.28 IPS |
|
|
Style Transfer (I8)
|
98% |
2437
3.21 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
346
12.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
337
12.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1180
42.2 IPS |
|
|
Text Classification (F32)
|
100% |
430
617.3 IPS |
|
|
Text Classification (F16)
|
100% |
438
629.6 IPS |
|
|
Text Classification (I8)
|
92% |
685
984.0 IPS |
|
|
Machine Translation (F32)
|
100% |
667
12.3 IPS |
|
|
Machine Translation (F16)
|
100% |
657
12.1 IPS |
|
|
Machine Translation (I8)
|
64% |
721
13.3 IPS |
