Samsung Galaxy S23 Plus
Geekbench ML Score
645
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 21 2024 05:19 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S23 Plus |
| Model ID | samsung SM-S916B |
| 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% |
299
55.9 IPS |
|
|
Image Classification (F16)
|
100% |
291
54.4 IPS |
|
|
Image Classification (I8)
|
97% |
746
139.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
361
6.03 IPS |
|
|
Image Segmentation (F16)
|
100% |
359
6.00 IPS |
|
|
Image Segmentation (I8)
|
98% |
738
12.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
493
0.60 IPS |
|
|
Pose Estimation (F16)
|
100% |
498
0.60 IPS |
|
|
Pose Estimation (I8)
|
100% |
1991
2.41 IPS |
|
|
Object Detection (F32)
|
100% |
309
23.1 IPS |
|
|
Object Detection (F16)
|
100% |
308
23.0 IPS |
|
|
Object Detection (I8)
|
61% |
851
63.6 IPS |
|
|
Face Detection (F32)
|
100% |
698
8.30 IPS |
|
|
Face Detection (F16)
|
100% |
693
8.25 IPS |
|
|
Face Detection (I8)
|
86% |
1593
18.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
618
4.79 IPS |
|
|
Depth Estimation (F16)
|
100% |
617
4.78 IPS |
|
|
Depth Estimation (I8)
|
95% |
1765
13.7 IPS |
|
|
Style Transfer (F32)
|
100% |
983
1.29 IPS |
|
|
Style Transfer (F16)
|
100% |
982
1.29 IPS |
|
|
Style Transfer (I8)
|
98% |
2426
3.19 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
346
12.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
349
12.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1226
43.8 IPS |
|
|
Text Classification (F32)
|
100% |
440
631.7 IPS |
|
|
Text Classification (F16)
|
100% |
446
640.4 IPS |
|
|
Text Classification (I8)
|
92% |
683
981.0 IPS |
|
|
Machine Translation (F32)
|
100% |
682
12.6 IPS |
|
|
Machine Translation (F16)
|
100% |
675
12.4 IPS |
|
|
Machine Translation (I8)
|
64% |
734
13.5 IPS |
