Samsung Galaxy Note 9
Geekbench ML Score
271
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.5.0 for Android AArch64
Result Information
| Upload Date | May 15 2023 09:49 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 | NNAPI |
| Device | |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
236
25.2 IPS |
|
|
Image Classification (F16)
|
100% |
305
32.7 IPS |
|
|
Image Classification (I8)
|
80% |
503
53.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
210
1.30 IPS |
|
|
Image Segmentation (F16)
|
100% |
251
1.55 IPS |
|
|
Image Segmentation (I8)
|
89% |
367
2.27 IPS |
|
|
Pose Estimation (F32)
|
100% |
284
1.15 IPS |
|
|
Pose Estimation (F16)
|
100% |
678
2.74 IPS |
|
|
Pose Estimation (I8)
|
80% |
214
0.86 IPS |
|
|
Object Detection (F32)
|
100% |
321
11.3 IPS |
|
|
Object Detection (F16)
|
100% |
342
12.0 IPS |
|
|
Object Detection (I8)
|
52% |
524
18.4 IPS |
|
|
Face Detection (F32)
|
100% |
586
6.73 IPS |
|
|
Face Detection (F16)
|
100% |
703
8.08 IPS |
|
|
Face Detection (I8)
|
75% |
1374
15.8 IPS |
|
|
Text Classification (F32)
|
100% |
18
7.02 IPS |
|
|
Text Classification (F16)
|
100% |
19
7.51 IPS |
|
|
Machine Translation (F32)
|
100% |
240
37.1 IPS |
|
|
Machine Translation (F16)
|
100% |
219
33.8 IPS |
