samsung SM-S711B
Geekbench ML Score
470
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 21 2024 10:28 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-S711B |
| Model ID | samsung SM-S711B |
| Motherboard | s5e9925 |
| Governor | energy_aware |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 2 part 3400 revision 0 |
| Base Frequency | 1.82 GHz |
| Cluster 1 | 4 Cores @ 1.82 GHz |
| Cluster 2 | 3 Cores @ 2.52 GHz |
| Cluster 3 | 1 Core @ 2.80 GHz |
| Memory Information | |
|---|---|
| Size | 7.12 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
266
49.9 IPS |
|
|
Image Classification (F16)
|
100% |
256
47.9 IPS |
|
|
Image Classification (I8)
|
97% |
325
60.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
258
4.31 IPS |
|
|
Image Segmentation (F16)
|
100% |
255
4.25 IPS |
|
|
Image Segmentation (I8)
|
98% |
300
5.02 IPS |
|
|
Pose Estimation (F32)
|
100% |
848
1.03 IPS |
|
|
Pose Estimation (F16)
|
100% |
849
1.03 IPS |
|
|
Pose Estimation (I8)
|
100% |
3003
3.64 IPS |
|
|
Object Detection (F32)
|
100% |
172
12.8 IPS |
|
|
Object Detection (F16)
|
100% |
172
12.8 IPS |
|
|
Object Detection (I8)
|
61% |
750
56.0 IPS |
|
|
Face Detection (F32)
|
100% |
369
4.38 IPS |
|
|
Face Detection (F16)
|
100% |
366
4.35 IPS |
|
|
Face Detection (I8)
|
86% |
531
6.31 IPS |
|
|
Depth Estimation (F32)
|
100% |
436
3.38 IPS |
|
|
Depth Estimation (F16)
|
100% |
456
3.53 IPS |
|
|
Depth Estimation (I8)
|
95% |
1086
8.42 IPS |
|
|
Style Transfer (F32)
|
100% |
1624
2.14 IPS |
|
|
Style Transfer (F16)
|
100% |
1562
2.06 IPS |
|
|
Style Transfer (I8)
|
98% |
2684
3.53 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
438
15.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
201
7.19 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
920
32.9 IPS |
|
|
Text Classification (F32)
|
100% |
506
727.8 IPS |
|
|
Text Classification (F16)
|
100% |
49
70.4 IPS |
|
|
Text Classification (I8)
|
92% |
417
599.9 IPS |
|
|
Machine Translation (F32)
|
100% |
732
13.5 IPS |
|
|
Machine Translation (F16)
|
100% |
321
5.91 IPS |
|
|
Machine Translation (I8)
|
64% |
345
6.35 IPS |
