samsung SM-S711B
Geekbench ML Score
417
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | April 03 2024 04:58 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% |
262
49.0 IPS |
|
|
Image Classification (F16)
|
100% |
258
48.3 IPS |
|
|
Image Classification (I8)
|
97% |
289
54.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
261
4.35 IPS |
|
|
Image Segmentation (F16)
|
100% |
255
4.25 IPS |
|
|
Image Segmentation (I8)
|
98% |
306
5.12 IPS |
|
|
Pose Estimation (F32)
|
100% |
842
1.02 IPS |
|
|
Pose Estimation (F16)
|
100% |
813
0.98 IPS |
|
|
Pose Estimation (I8)
|
100% |
3243
3.93 IPS |
|
|
Object Detection (F32)
|
100% |
213
15.9 IPS |
|
|
Object Detection (F16)
|
100% |
178
13.3 IPS |
|
|
Object Detection (I8)
|
61% |
757
56.5 IPS |
|
|
Face Detection (F32)
|
100% |
377
4.48 IPS |
|
|
Face Detection (F16)
|
100% |
364
4.32 IPS |
|
|
Face Detection (I8)
|
86% |
589
7.01 IPS |
|
|
Depth Estimation (F32)
|
100% |
462
3.58 IPS |
|
|
Depth Estimation (F16)
|
100% |
458
3.55 IPS |
|
|
Depth Estimation (I8)
|
95% |
780
6.05 IPS |
|
|
Style Transfer (F32)
|
100% |
1477
1.94 IPS |
|
|
Style Transfer (F16)
|
100% |
1469
1.93 IPS |
|
|
Style Transfer (I8)
|
98% |
2715
3.57 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
518
18.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
624
22.3 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
433
15.5 IPS |
|
|
Text Classification (F32)
|
100% |
45
65.4 IPS |
|
|
Text Classification (F16)
|
100% |
48
68.9 IPS |
|
|
Text Classification (I8)
|
92% |
386
555.2 IPS |
|
|
Machine Translation (F32)
|
100% |
386
7.10 IPS |
|
|
Machine Translation (F16)
|
100% |
331
6.09 IPS |
|
|
Machine Translation (I8)
|
64% |
136
2.51 IPS |
