samsung SM-S928B
Geekbench ML Score
660
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | April 27 2024 08:41 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-S928B |
| Model ID | samsung SM-S928B |
| Motherboard | pineapple |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.26 GHz |
| Cluster 1 | 2 Cores @ 2.27 GHz |
| Cluster 2 | 2 Cores @ 2.96 GHz |
| Cluster 3 | 3 Cores @ 3.15 GHz |
| Cluster 4 | 1 Core @ 3.40 GHz |
| Memory Information | |
|---|---|
| Size | 10.81 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
307
57.4 IPS |
|
|
Image Classification (F16)
|
100% |
302
56.5 IPS |
|
|
Image Classification (I8)
|
97% |
790
147.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
368
6.14 IPS |
|
|
Image Segmentation (F16)
|
100% |
367
6.12 IPS |
|
|
Image Segmentation (I8)
|
98% |
760
12.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
500
0.61 IPS |
|
|
Pose Estimation (F16)
|
100% |
491
0.59 IPS |
|
|
Pose Estimation (I8)
|
100% |
1999
2.42 IPS |
|
|
Object Detection (F32)
|
100% |
311
23.2 IPS |
|
|
Object Detection (F16)
|
100% |
313
23.4 IPS |
|
|
Object Detection (I8)
|
61% |
842
62.8 IPS |
|
|
Face Detection (F32)
|
100% |
718
8.54 IPS |
|
|
Face Detection (F16)
|
100% |
710
8.45 IPS |
|
|
Face Detection (I8)
|
86% |
1729
20.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
631
4.89 IPS |
|
|
Depth Estimation (F16)
|
100% |
628
4.87 IPS |
|
|
Depth Estimation (I8)
|
95% |
1797
13.9 IPS |
|
|
Style Transfer (F32)
|
100% |
1007
1.32 IPS |
|
|
Style Transfer (F16)
|
100% |
998
1.31 IPS |
|
|
Style Transfer (I8)
|
98% |
2489
3.27 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
354
12.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
357
12.7 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1236
44.1 IPS |
|
|
Text Classification (F32)
|
100% |
428
615.0 IPS |
|
|
Text Classification (F16)
|
100% |
430
617.4 IPS |
|
|
Text Classification (I8)
|
92% |
706
1.02 KIPS |
|
|
Machine Translation (F32)
|
100% |
708
13.0 IPS |
|
|
Machine Translation (F16)
|
100% |
702
12.9 IPS |
|
|
Machine Translation (I8)
|
64% |
818
15.1 IPS |
