Samsung Galaxy S23 Plus
Geekbench ML Score
515
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 08 2024 01:41 PM |
| Views | 4 |
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% |
294
54.9 IPS |
|
|
Image Classification (F16)
|
100% |
281
52.7 IPS |
|
|
Image Classification (I8)
|
97% |
706
132.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
336
5.61 IPS |
|
|
Image Segmentation (F16)
|
100% |
335
5.60 IPS |
|
|
Image Segmentation (I8)
|
98% |
695
11.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
452
0.55 IPS |
|
|
Pose Estimation (F16)
|
100% |
453
0.55 IPS |
|
|
Pose Estimation (I8)
|
100% |
1580
1.91 IPS |
|
|
Object Detection (F32)
|
100% |
232
17.3 IPS |
|
|
Object Detection (F16)
|
100% |
233
17.4 IPS |
|
|
Object Detection (I8)
|
61% |
596
44.5 IPS |
|
|
Face Detection (F32)
|
100% |
573
6.81 IPS |
|
|
Face Detection (F16)
|
100% |
553
6.57 IPS |
|
|
Face Detection (I8)
|
86% |
1136
13.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
482
3.74 IPS |
|
|
Depth Estimation (F16)
|
100% |
483
3.75 IPS |
|
|
Depth Estimation (I8)
|
95% |
1296
10.1 IPS |
|
|
Style Transfer (F32)
|
100% |
773
1.02 IPS |
|
|
Style Transfer (F16)
|
100% |
772
1.02 IPS |
|
|
Style Transfer (I8)
|
98% |
1832
2.41 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
261
9.31 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
265
9.48 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
935
33.4 IPS |
|
|
Text Classification (F32)
|
100% |
312
447.9 IPS |
|
|
Text Classification (F16)
|
100% |
312
447.7 IPS |
|
|
Text Classification (I8)
|
92% |
451
648.8 IPS |
|
|
Machine Translation (F32)
|
100% |
539
9.93 IPS |
|
|
Machine Translation (F16)
|
100% |
531
9.77 IPS |
|
|
Machine Translation (I8)
|
64% |
517
9.51 IPS |
