samsung SM-S921B
Geekbench ML Score
607
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 18 2024 08:58 AM |
| Views | 3 |
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% |
278
52.1 IPS |
|
|
Image Classification (F16)
|
100% |
318
59.4 IPS |
|
|
Image Classification (I8)
|
97% |
526
98.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
402
6.72 IPS |
|
|
Image Segmentation (F16)
|
100% |
409
6.82 IPS |
|
|
Image Segmentation (I8)
|
98% |
435
7.27 IPS |
|
|
Pose Estimation (F32)
|
100% |
943
1.14 IPS |
|
|
Pose Estimation (F16)
|
100% |
965
1.17 IPS |
|
|
Pose Estimation (I8)
|
100% |
3300
4.00 IPS |
|
|
Object Detection (F32)
|
100% |
332
24.8 IPS |
|
|
Object Detection (F16)
|
100% |
355
26.5 IPS |
|
|
Object Detection (I8)
|
61% |
602
44.9 IPS |
|
|
Face Detection (F32)
|
100% |
786
9.35 IPS |
|
|
Face Detection (F16)
|
100% |
820
9.75 IPS |
|
|
Face Detection (I8)
|
86% |
1108
13.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
802
6.22 IPS |
|
|
Depth Estimation (F16)
|
100% |
828
6.42 IPS |
|
|
Depth Estimation (I8)
|
95% |
1142
8.85 IPS |
|
|
Style Transfer (F32)
|
100% |
1655
2.18 IPS |
|
|
Style Transfer (F16)
|
100% |
1740
2.29 IPS |
|
|
Style Transfer (I8)
|
98% |
2633
3.46 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
384
13.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
481
17.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
941
33.6 IPS |
|
|
Text Classification (F32)
|
100% |
285
410.2 IPS |
|
|
Text Classification (F16)
|
100% |
247
355.1 IPS |
|
|
Text Classification (I8)
|
92% |
176
252.8 IPS |
|
|
Machine Translation (F32)
|
100% |
560
10.3 IPS |
|
|
Machine Translation (F16)
|
100% |
513
9.43 IPS |
|
|
Machine Translation (I8)
|
64% |
174
3.21 IPS |
