samsung SM-S711B
Geekbench ML Score
450
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | April 26 2024 06:50 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% |
213
39.8 IPS |
|
|
Image Classification (F16)
|
100% |
152
28.4 IPS |
|
|
Image Classification (I8)
|
97% |
397
74.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
254
4.24 IPS |
|
|
Image Segmentation (F16)
|
100% |
252
4.21 IPS |
|
|
Image Segmentation (I8)
|
98% |
297
4.95 IPS |
|
|
Pose Estimation (F32)
|
100% |
783
0.95 IPS |
|
|
Pose Estimation (F16)
|
100% |
794
0.96 IPS |
|
|
Pose Estimation (I8)
|
100% |
2324
2.81 IPS |
|
|
Object Detection (F32)
|
100% |
176
13.2 IPS |
|
|
Object Detection (F16)
|
100% |
222
16.6 IPS |
|
|
Object Detection (I8)
|
61% |
522
39.0 IPS |
|
|
Face Detection (F32)
|
100% |
364
4.33 IPS |
|
|
Face Detection (F16)
|
100% |
378
4.49 IPS |
|
|
Face Detection (I8)
|
86% |
547
6.50 IPS |
|
|
Depth Estimation (F32)
|
100% |
416
3.23 IPS |
|
|
Depth Estimation (F16)
|
100% |
453
3.51 IPS |
|
|
Depth Estimation (I8)
|
95% |
754
5.85 IPS |
|
|
Style Transfer (F32)
|
100% |
1435
1.89 IPS |
|
|
Style Transfer (F16)
|
100% |
1400
1.84 IPS |
|
|
Style Transfer (I8)
|
98% |
2611
3.43 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
336
12.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
600
21.4 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
775
27.7 IPS |
|
|
Text Classification (F32)
|
100% |
409
588.4 IPS |
|
|
Text Classification (F16)
|
100% |
485
696.8 IPS |
|
|
Text Classification (I8)
|
92% |
87
124.6 IPS |
|
|
Machine Translation (F32)
|
100% |
325
5.97 IPS |
|
|
Machine Translation (F16)
|
100% |
395
7.27 IPS |
|
|
Machine Translation (I8)
|
64% |
285
5.25 IPS |
