samsung SM-S928B
Geekbench ML Score
650
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 01 2024 09:26 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% |
298
55.8 IPS |
|
|
Image Classification (F16)
|
100% |
291
54.4 IPS |
|
|
Image Classification (I8)
|
97% |
779
145.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
360
6.02 IPS |
|
|
Image Segmentation (F16)
|
100% |
360
6.01 IPS |
|
|
Image Segmentation (I8)
|
98% |
756
12.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
492
0.60 IPS |
|
|
Pose Estimation (F16)
|
100% |
490
0.59 IPS |
|
|
Pose Estimation (I8)
|
100% |
2001
2.42 IPS |
|
|
Object Detection (F32)
|
100% |
308
23.0 IPS |
|
|
Object Detection (F16)
|
100% |
303
22.6 IPS |
|
|
Object Detection (I8)
|
61% |
835
62.3 IPS |
|
|
Face Detection (F32)
|
100% |
719
8.55 IPS |
|
|
Face Detection (F16)
|
100% |
710
8.44 IPS |
|
|
Face Detection (I8)
|
86% |
1717
20.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
622
4.82 IPS |
|
|
Depth Estimation (F16)
|
100% |
618
4.79 IPS |
|
|
Depth Estimation (I8)
|
95% |
1770
13.7 IPS |
|
|
Style Transfer (F32)
|
100% |
986
1.30 IPS |
|
|
Style Transfer (F16)
|
100% |
990
1.30 IPS |
|
|
Style Transfer (I8)
|
98% |
2459
3.23 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
346
12.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
355
12.7 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1206
43.1 IPS |
|
|
Text Classification (F32)
|
100% |
426
611.7 IPS |
|
|
Text Classification (F16)
|
100% |
423
608.1 IPS |
|
|
Text Classification (I8)
|
92% |
688
988.1 IPS |
|
|
Machine Translation (F32)
|
100% |
699
12.9 IPS |
|
|
Machine Translation (F16)
|
100% |
688
12.7 IPS |
|
|
Machine Translation (I8)
|
64% |
803
14.8 IPS |
