Samsung Galaxy S23
Geekbench ML Score
608
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | April 13 2024 08:18 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy S23 |
| Model ID | samsung SM-S911B |
| 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% |
286
53.5 IPS |
|
|
Image Classification (F16)
|
100% |
280
52.4 IPS |
|
|
Image Classification (I8)
|
97% |
703
131.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
339
5.66 IPS |
|
|
Image Segmentation (F16)
|
100% |
336
5.60 IPS |
|
|
Image Segmentation (I8)
|
98% |
711
11.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
469
0.57 IPS |
|
|
Pose Estimation (F16)
|
100% |
464
0.56 IPS |
|
|
Pose Estimation (I8)
|
100% |
1894
2.29 IPS |
|
|
Object Detection (F32)
|
100% |
295
22.0 IPS |
|
|
Object Detection (F16)
|
100% |
296
22.1 IPS |
|
|
Object Detection (I8)
|
61% |
822
61.4 IPS |
|
|
Face Detection (F32)
|
100% |
667
7.92 IPS |
|
|
Face Detection (F16)
|
100% |
657
7.81 IPS |
|
|
Face Detection (I8)
|
86% |
1492
17.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
585
4.54 IPS |
|
|
Depth Estimation (F16)
|
100% |
582
4.51 IPS |
|
|
Depth Estimation (I8)
|
95% |
1713
13.3 IPS |
|
|
Style Transfer (F32)
|
100% |
923
1.21 IPS |
|
|
Style Transfer (F16)
|
100% |
931
1.22 IPS |
|
|
Style Transfer (I8)
|
98% |
2328
3.06 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
332
11.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
335
12.0 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1207
43.1 IPS |
|
|
Text Classification (F32)
|
100% |
405
582.5 IPS |
|
|
Text Classification (F16)
|
100% |
405
582.0 IPS |
|
|
Text Classification (I8)
|
92% |
578
831.0 IPS |
|
|
Machine Translation (F32)
|
100% |
645
11.9 IPS |
|
|
Machine Translation (F16)
|
100% |
645
11.9 IPS |
|
|
Machine Translation (I8)
|
64% |
626
11.5 IPS |
