samsung SM-S921B
Geekbench ML Score
501
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | March 28 2024 03:37 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-S921B |
| Model ID | samsung SM-S921B |
| Motherboard | s5e9945 |
| Governor | energy_aware |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 10 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 1.96 GHz |
| Cluster 1 | 4 Cores @ 1.96 GHz |
| Cluster 2 | 3 Cores @ 2.59 GHz |
| Cluster 3 | 2 Cores @ 2.90 GHz |
| Cluster 4 | 1 Core @ 3.21 GHz |
| Memory Information | |
|---|---|
| Size | 7.06 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
291
54.4 IPS |
|
|
Image Classification (F16)
|
100% |
286
53.5 IPS |
|
|
Image Classification (I8)
|
97% |
727
136.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
808
13.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
1228
20.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
737
12.3 IPS |
|
|
Pose Estimation (F32)
|
0
|
||
|
Pose Estimation (F16)
|
0
|
||
|
Pose Estimation (I8)
|
100% |
1911
2.31 IPS |
|
|
Object Detection (F32)
|
100% |
296
22.1 IPS |
|
|
Object Detection (F16)
|
100% |
293
21.9 IPS |
|
|
Object Detection (I8)
|
61% |
813
60.7 IPS |
|
|
Face Detection (F32)
|
100% |
674
8.02 IPS |
|
|
Face Detection (F16)
|
100% |
668
7.95 IPS |
|
|
Face Detection (I8)
|
86% |
1636
19.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
602
4.67 IPS |
|
|
Depth Estimation (F16)
|
100% |
604
4.68 IPS |
|
|
Depth Estimation (I8)
|
95% |
1723
13.4 IPS |
|
|
Style Transfer (F32)
|
100% |
954
1.26 IPS |
|
|
Style Transfer (F16)
|
100% |
947
1.25 IPS |
|
|
Style Transfer (I8)
|
98% |
2284
3.00 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1768
63.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2215
79.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1214
43.3 IPS |
|
|
Text Classification (F32)
|
100% |
410
589.5 IPS |
|
|
Text Classification (F16)
|
100% |
415
596.8 IPS |
|
|
Text Classification (I8)
|
92% |
699
1.00 KIPS |
|
|
Machine Translation (F32)
|
100% |
645
11.9 IPS |
|
|
Machine Translation (F16)
|
100% |
634
11.7 IPS |
|
|
Machine Translation (I8)
|
64% |
765
14.1 IPS |
