Samsung Galaxy Note 8
Geekbench ML Score
163
TensorFlow Lite CPU Inference Score
Geekbench ML 0.5.0 for Android AArch64
Result Information
| Upload Date | June 13 2021 05:40 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 9 |
| Model | Samsung Galaxy Note 8 |
| Model ID | samsung SM-N950F |
| Motherboard | universal8895 |
| Governor | interactive |
| CPU Information | |
|---|---|
| Name | ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 83 architecture 8 variant 4 part 1 revision 0 |
| Base Frequency | 1.69 GHz |
| Cluster 1 | 4 Cores @ 1.69 GHz |
| Cluster 2 | 4 Cores @ 2.31 GHz |
| Memory Information | |
|---|---|
| Size | 5.24 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
144
15.4 IPS |
|
|
Image Classification (F16)
|
100% |
138
14.8 IPS |
|
|
Image Classification (I8)
|
81% |
117
12.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
248
1.53 IPS |
|
|
Image Segmentation (F16)
|
100% |
270
1.67 IPS |
|
|
Image Segmentation (I8)
|
89% |
434
2.68 IPS |
|
|
Pose Estimation (F32)
|
100% |
95
0.38 IPS |
|
|
Pose Estimation (F16)
|
100% |
93
0.38 IPS |
|
|
Pose Estimation (I8)
|
80% |
130
0.52 IPS |
|
|
Object Detection (F32)
|
100% |
120
4.22 IPS |
|
|
Object Detection (F16)
|
100% |
106
3.73 IPS |
|
|
Object Detection (I8)
|
52% |
167
5.88 IPS |
|
|
Face Detection (F32)
|
100% |
287
3.30 IPS |
|
|
Face Detection (F16)
|
100% |
267
3.06 IPS |
|
|
Face Detection (I8)
|
75% |
300
3.45 IPS |
|
|
Text Classification (F32)
|
100% |
193
76.5 IPS |
|
|
Text Classification (F16)
|
100% |
150
59.3 IPS |
|
|
Machine Translation (F32)
|
100% |
103
15.9 IPS |
|
|
Machine Translation (F16)
|
100% |
102
15.7 IPS |
