Samsung Galaxy S23
Geekbench ML Score
626
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| User | korbs |
| Upload Date | July 25 2024 09:13 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S23 |
| Model ID | samsung SM-S911U |
| 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 | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
295
55.2 IPS |
|
|
Image Classification (F16)
|
100% |
293
54.9 IPS |
|
|
Image Classification (I8)
|
97% |
715
133.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
355
5.92 IPS |
|
|
Image Segmentation (F16)
|
100% |
352
5.88 IPS |
|
|
Image Segmentation (I8)
|
98% |
735
12.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
485
0.59 IPS |
|
|
Pose Estimation (F16)
|
100% |
477
0.58 IPS |
|
|
Pose Estimation (I8)
|
100% |
2052
2.49 IPS |
|
|
Object Detection (F32)
|
100% |
303
22.6 IPS |
|
|
Object Detection (F16)
|
100% |
302
22.6 IPS |
|
|
Object Detection (I8)
|
61% |
823
61.5 IPS |
|
|
Face Detection (F32)
|
100% |
671
7.98 IPS |
|
|
Face Detection (F16)
|
100% |
676
8.04 IPS |
|
|
Face Detection (I8)
|
86% |
1527
18.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
589
4.56 IPS |
|
|
Depth Estimation (F16)
|
100% |
602
4.67 IPS |
|
|
Depth Estimation (I8)
|
95% |
1757
13.6 IPS |
|
|
Style Transfer (F32)
|
100% |
933
1.23 IPS |
|
|
Style Transfer (F16)
|
100% |
941
1.24 IPS |
|
|
Style Transfer (I8)
|
98% |
2334
3.07 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
344
12.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
334
11.9 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1231
44.0 IPS |
|
|
Text Classification (F32)
|
100% |
421
605.8 IPS |
|
|
Text Classification (F16)
|
100% |
421
604.9 IPS |
|
|
Text Classification (I8)
|
92% |
600
862.4 IPS |
|
|
Machine Translation (F32)
|
100% |
662
12.2 IPS |
|
|
Machine Translation (F16)
|
100% |
647
11.9 IPS |
|
|
Machine Translation (I8)
|
64% |
699
12.9 IPS |
