Samsung Galaxy Note 8
Geekbench ML Score
148
TensorFlow Lite CPU Inference Score
Geekbench ML 0.5.2 for Android AArch64
Result Information
| Upload Date | December 27 2024 02:37 PM |
| Views | 4 |
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 | 5.21 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
89
9.51 IPS |
|
|
Image Classification (F16)
|
100% |
110
11.8 IPS |
|
|
Image Classification (I8)
|
81% |
112
12.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
191
1.18 IPS |
|
|
Image Segmentation (F16)
|
100% |
193
1.19 IPS |
|
|
Image Segmentation (I8)
|
89% |
453
2.80 IPS |
|
|
Pose Estimation (F32)
|
100% |
112
0.45 IPS |
|
|
Pose Estimation (F16)
|
100% |
108
0.44 IPS |
|
|
Pose Estimation (I8)
|
80% |
132
0.54 IPS |
|
|
Object Detection (F32)
|
100% |
107
3.76 IPS |
|
|
Object Detection (F16)
|
100% |
101
3.55 IPS |
|
|
Object Detection (I8)
|
52% |
189
6.62 IPS |
|
|
Face Detection (F32)
|
100% |
195
2.24 IPS |
|
|
Face Detection (F16)
|
100% |
189
2.17 IPS |
|
|
Face Detection (I8)
|
75% |
271
3.11 IPS |
|
|
Text Classification (F32)
|
100% |
160
63.1 IPS |
|
|
Text Classification (F16)
|
100% |
171
67.6 IPS |
|
|
Machine Translation (F32)
|
100% |
108
16.7 IPS |
|
|
Machine Translation (F16)
|
100% |
108
16.7 IPS |
