samsung SM-S928B
Geekbench ML Score
682
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | August 20 2024 01:44 PM |
| 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% |
309
57.9 IPS |
|
|
Image Classification (F16)
|
100% |
308
57.6 IPS |
|
|
Image Classification (I8)
|
97% |
796
149.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
384
6.42 IPS |
|
|
Image Segmentation (F16)
|
100% |
382
6.38 IPS |
|
|
Image Segmentation (I8)
|
98% |
778
13.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
542
0.66 IPS |
|
|
Pose Estimation (F16)
|
100% |
535
0.65 IPS |
|
|
Pose Estimation (I8)
|
100% |
2078
2.52 IPS |
|
|
Object Detection (F32)
|
100% |
321
24.0 IPS |
|
|
Object Detection (F16)
|
100% |
319
23.8 IPS |
|
|
Object Detection (I8)
|
61% |
865
64.6 IPS |
|
|
Face Detection (F32)
|
100% |
762
9.06 IPS |
|
|
Face Detection (F16)
|
100% |
754
8.97 IPS |
|
|
Face Detection (I8)
|
86% |
1765
21.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
668
5.18 IPS |
|
|
Depth Estimation (F16)
|
100% |
666
5.16 IPS |
|
|
Depth Estimation (I8)
|
95% |
1849
14.3 IPS |
|
|
Style Transfer (F32)
|
100% |
1038
1.37 IPS |
|
|
Style Transfer (F16)
|
100% |
1031
1.36 IPS |
|
|
Style Transfer (I8)
|
98% |
2589
3.41 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
366
13.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
368
13.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1254
44.8 IPS |
|
|
Text Classification (F32)
|
100% |
435
624.5 IPS |
|
|
Text Classification (F16)
|
100% |
437
628.4 IPS |
|
|
Text Classification (I8)
|
92% |
719
1.03 KIPS |
|
|
Machine Translation (F32)
|
100% |
726
13.4 IPS |
|
|
Machine Translation (F16)
|
100% |
715
13.2 IPS |
|
|
Machine Translation (I8)
|
64% |
832
15.3 IPS |
