samsung SM-S711B
Geekbench ML Score
1120
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | April 03 2024 05:05 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
379
71.0 IPS |
|
|
Image Classification (F16)
|
100% |
436
81.5 IPS |
|
|
Image Classification (I8)
|
99% |
407
76.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
1210
20.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
1500
25.0 IPS |
|
|
Image Segmentation (I8)
|
98% |
1472
24.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
1969
2.38 IPS |
|
|
Pose Estimation (F16)
|
100% |
2612
3.16 IPS |
|
|
Pose Estimation (I8)
|
100% |
2797
3.39 IPS |
|
|
Object Detection (F32)
|
100% |
419
31.3 IPS |
|
|
Object Detection (F16)
|
100% |
274
20.5 IPS |
|
|
Object Detection (I8)
|
58% |
300
22.4 IPS |
|
|
Face Detection (F32)
|
100% |
1876
22.3 IPS |
|
|
Face Detection (F16)
|
97% |
1932
23.0 IPS |
|
|
Face Detection (I8)
|
86% |
1821
21.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
2135
16.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
2763
21.4 IPS |
|
|
Depth Estimation (I8)
|
95% |
2749
21.3 IPS |
|
|
Style Transfer (F32)
|
100% |
6012
7.91 IPS |
|
|
Style Transfer (F16)
|
100% |
8664
11.4 IPS |
|
|
Style Transfer (I8)
|
98% |
8814
11.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1149
41.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1429
51.0 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1452
51.9 IPS |
|
|
Text Classification (F32)
|
100% |
246
353.7 IPS |
|
|
Text Classification (F16)
|
100% |
246
353.1 IPS |
|
|
Text Classification (I8)
|
92% |
460
661.7 IPS |
|
|
Machine Translation (F32)
|
100% |
430
7.91 IPS |
|
|
Machine Translation (F16)
|
100% |
429
7.89 IPS |
|
|
Machine Translation (I8)
|
64% |
564
10.4 IPS |
