Samsung Galaxy S6
Geekbench ML Score
141
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | August 25 2024 04:46 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Samsung Galaxy S6 |
| Model ID | samsung SM-G920F |
| Motherboard | universal7420 |
| Governor | interactive |
| CPU Information | |
|---|---|
| Name | ARM SAMSUNG |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 variant 1 part 3335 revision 0 |
| Base Frequency | 1.50 GHz |
| Cluster 1 | 4 Cores @ 1.50 GHz |
| Cluster 2 | 4 Cores @ 2.10 GHz |
| Memory Information | |
|---|---|
| Size | 2.63 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
77
14.4 IPS |
|
|
Image Classification (F16)
|
100% |
75
14.0 IPS |
|
|
Image Classification (I8)
|
97% |
93
17.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
113
1.88 IPS |
|
|
Image Segmentation (F16)
|
100% |
119
1.99 IPS |
|
|
Image Segmentation (I8)
|
98% |
139
2.33 IPS |
|
|
Pose Estimation (F32)
|
100% |
142
0.17 IPS |
|
|
Pose Estimation (F16)
|
100% |
138
0.17 IPS |
|
|
Pose Estimation (I8)
|
100% |
360
0.44 IPS |
|
|
Object Detection (F32)
|
100% |
72
5.40 IPS |
|
|
Object Detection (F16)
|
100% |
75
5.62 IPS |
|
|
Object Detection (I8)
|
61% |
113
8.46 IPS |
|
|
Face Detection (F32)
|
100% |
192
2.28 IPS |
|
|
Face Detection (F16)
|
100% |
179
2.13 IPS |
|
|
Face Detection (I8)
|
86% |
299
3.56 IPS |
|
|
Depth Estimation (F32)
|
100% |
157
1.22 IPS |
|
|
Depth Estimation (F16)
|
100% |
152
1.18 IPS |
|
|
Depth Estimation (I8)
|
95% |
280
2.17 IPS |
|
|
Style Transfer (F32)
|
100% |
259
0.34 IPS |
|
|
Style Transfer (F16)
|
100% |
267
0.35 IPS |
|
|
Style Transfer (I8)
|
98% |
689
0.91 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
88
3.15 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
88
3.13 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
169
6.05 IPS |
|
|
Text Classification (F32)
|
100% |
128
184.4 IPS |
|
|
Text Classification (F16)
|
100% |
124
178.6 IPS |
|
|
Text Classification (I8)
|
92% |
109
156.1 IPS |
|
|
Machine Translation (F32)
|
100% |
130
2.40 IPS |
|
|
Machine Translation (F16)
|
100% |
107
1.97 IPS |
|
|
Machine Translation (I8)
|
64% |
74
1.35 IPS |
