Samsung Galaxy Note 9
Geekbench ML Score
630
TensorFlow Lite GPU Inference Score
Geekbench ML 0.5.2 for Android AArch64
Result Information
| Upload Date | January 15 2025 08:33 AM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Android 10 |
| Model | Samsung Galaxy Note 9 |
| Model ID | samsung SM-N960U |
| 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 | GPU |
| Device | |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
396
42.4 IPS |
|
|
Image Classification (F16)
|
100% |
658
70.5 IPS |
|
|
Image Classification (I8)
|
80% |
581
62.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
1160
7.16 IPS |
|
|
Image Segmentation (F16)
|
100% |
1740
10.7 IPS |
|
|
Image Segmentation (I8)
|
89% |
2062
12.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
517
2.09 IPS |
|
|
Pose Estimation (F16)
|
100% |
942
3.81 IPS |
|
|
Pose Estimation (I8)
|
80% |
984
3.98 IPS |
|
|
Object Detection (F32)
|
100% |
358
12.5 IPS |
|
|
Object Detection (F16)
|
99% |
496
17.4 IPS |
|
|
Object Detection (I8)
|
53% |
444
15.6 IPS |
|
|
Face Detection (F32)
|
100% |
894
10.3 IPS |
|
|
Face Detection (F16)
|
97% |
1324
15.2 IPS |
|
|
Face Detection (I8)
|
76% |
1176
13.5 IPS |
|
|
Text Classification (F32)
|
100% |
331
130.9 IPS |
|
|
Text Classification (F16)
|
98% |
378
149.7 IPS |
|
|
Machine Translation (F32)
|
100% |
200
30.8 IPS |
|
|
Machine Translation (F16)
|
100% |
189
29.2 IPS |
