samsung SM-S928U1
Geekbench ML Score
597
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 08 2024 03:17 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-S928U1 |
| Model ID | samsung SM-S928U1 |
| 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% |
269
50.4 IPS |
|
|
Image Classification (F16)
|
100% |
269
50.4 IPS |
|
|
Image Classification (I8)
|
97% |
692
129.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
335
5.59 IPS |
|
|
Image Segmentation (F16)
|
100% |
333
5.57 IPS |
|
|
Image Segmentation (I8)
|
98% |
695
11.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
471
0.57 IPS |
|
|
Pose Estimation (F16)
|
100% |
470
0.57 IPS |
|
|
Pose Estimation (I8)
|
100% |
1806
2.19 IPS |
|
|
Object Detection (F32)
|
100% |
282
21.0 IPS |
|
|
Object Detection (F16)
|
100% |
282
21.0 IPS |
|
|
Object Detection (I8)
|
61% |
726
54.2 IPS |
|
|
Face Detection (F32)
|
100% |
668
7.94 IPS |
|
|
Face Detection (F16)
|
100% |
668
7.94 IPS |
|
|
Face Detection (I8)
|
86% |
1486
17.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
580
4.50 IPS |
|
|
Depth Estimation (F16)
|
100% |
582
4.51 IPS |
|
|
Depth Estimation (I8)
|
95% |
1621
12.6 IPS |
|
|
Style Transfer (F32)
|
100% |
925
1.22 IPS |
|
|
Style Transfer (F16)
|
100% |
929
1.22 IPS |
|
|
Style Transfer (I8)
|
98% |
2216
2.91 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
330
11.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
338
12.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1118
39.9 IPS |
|
|
Text Classification (F32)
|
100% |
377
541.4 IPS |
|
|
Text Classification (F16)
|
100% |
367
528.0 IPS |
|
|
Text Classification (I8)
|
92% |
603
867.2 IPS |
|
|
Machine Translation (F32)
|
100% |
643
11.8 IPS |
|
|
Machine Translation (F16)
|
100% |
645
11.9 IPS |
|
|
Machine Translation (I8)
|
64% |
727
13.4 IPS |
