Samsung Galaxy Note 9
Geekbench ML Score
219
TensorFlow Lite CPU Inference Score
Geekbench ML 0.5.0 for Android AArch64
Result Information
| Upload Date | May 15 2023 09:45 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 10 |
| Model | Samsung Galaxy Note 9 |
| Model ID | samsung SM-N960U1 |
| Motherboard | sdm845 |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | Qualcomm Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 6 part 2050 revision 13 |
| Base Frequency | 1.77 GHz |
| Cluster 1 | 4 Cores @ 1.77 GHz |
| Cluster 2 | 4 Cores @ 2.80 GHz |
| Memory Information | |
|---|---|
| Size | 5.45 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
154
16.5 IPS |
|
|
Image Classification (F16)
|
100% |
153
16.4 IPS |
|
|
Image Classification (I8)
|
81% |
167
17.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
329
2.03 IPS |
|
|
Image Segmentation (F16)
|
100% |
318
1.96 IPS |
|
|
Image Segmentation (I8)
|
89% |
635
3.92 IPS |
|
|
Pose Estimation (F32)
|
100% |
122
0.49 IPS |
|
|
Pose Estimation (F16)
|
100% |
118
0.48 IPS |
|
|
Pose Estimation (I8)
|
80% |
182
0.74 IPS |
|
|
Object Detection (F32)
|
100% |
214
7.51 IPS |
|
|
Object Detection (F16)
|
100% |
224
7.86 IPS |
|
|
Object Detection (I8)
|
52% |
237
8.32 IPS |
|
|
Face Detection (F32)
|
100% |
313
3.59 IPS |
|
|
Face Detection (F16)
|
100% |
315
3.62 IPS |
|
|
Face Detection (I8)
|
75% |
413
4.75 IPS |
|
|
Text Classification (F32)
|
100% |
162
64.1 IPS |
|
|
Text Classification (F16)
|
100% |
163
64.3 IPS |
|
|
Machine Translation (F32)
|
100% |
197
30.4 IPS |
|
|
Machine Translation (F16)
|
100% |
191
29.5 IPS |
