samsung SM-S921B
Geekbench ML Score
998
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | October 17 2024 08:50 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
530
99.1 IPS |
|
|
Image Classification (F16)
|
100% |
508
95.1 IPS |
|
|
Image Classification (I8)
|
97% |
930
174.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
752
12.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
735
12.3 IPS |
|
|
Image Segmentation (I8)
|
98% |
924
15.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
1324
1.60 IPS |
|
|
Pose Estimation (F16)
|
100% |
1210
1.47 IPS |
|
|
Pose Estimation (I8)
|
100% |
5805
7.03 IPS |
|
|
Object Detection (F32)
|
100% |
585
43.6 IPS |
|
|
Object Detection (F16)
|
100% |
583
43.5 IPS |
|
|
Object Detection (I8)
|
61% |
1292
96.5 IPS |
|
|
Face Detection (F32)
|
100% |
1336
15.9 IPS |
|
|
Face Detection (F16)
|
100% |
1237
14.7 IPS |
|
|
Face Detection (I8)
|
86% |
1919
22.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
1385
10.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
1314
10.2 IPS |
|
|
Depth Estimation (I8)
|
95% |
1899
14.7 IPS |
|
|
Style Transfer (F32)
|
100% |
2332
3.07 IPS |
|
|
Style Transfer (F16)
|
100% |
2153
2.83 IPS |
|
|
Style Transfer (I8)
|
98% |
3404
4.48 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
653
23.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
626
22.4 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1587
56.7 IPS |
|
|
Text Classification (F32)
|
100% |
448
643.9 IPS |
|
|
Text Classification (F16)
|
100% |
454
652.4 IPS |
|
|
Text Classification (I8)
|
92% |
271
388.8 IPS |
|
|
Machine Translation (F32)
|
100% |
1024
18.8 IPS |
|
|
Machine Translation (F16)
|
100% |
915
16.8 IPS |
|
|
Machine Translation (I8)
|
64% |
293
5.40 IPS |
