| User | VenomF5 |
| Upload Date | July 25 2025 12:32 AM |
| Views | 10 |
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Qualcomm ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | samsung SM-F966U1 |
| Model ID | samsung SM-F966U1 |
| Motherboard | sun |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | Qualcomm ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 3 part 1 revision 4 |
| Base Frequency | 3.53 GHz |
| Cluster 1 | 6 Cores @ 3.53 GHz |
| Cluster 2 | 2 Cores @ 4.47 GHz |
| Memory Information | |
|---|---|
| Size | 14.75 GB |
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1781
331.3 IPS |
|
|
Image Classification (HP)
|
100% |
2638
490.6 IPS |
|
|
Image Classification (Q)
|
100% |
2807
522.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
3098
50.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
6707
108.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
5778
93.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
13766
16.1 IPS |
|
|
Pose Estimation (HP)
|
99% |
24689
28.8 IPS |
|
|
Pose Estimation (Q)
|
95% |
16190
19.0 IPS |
|
|
Object Detection (SP)
|
100% |
1002
79.5 IPS |
|
|
Object Detection (HP)
|
99% |
1122
89.0 IPS |
|
|
Object Detection (Q)
|
85% |
1092
87.9 IPS |
|
|
Face Detection (SP)
|
100% |
3580
42.5 IPS |
|
|
Face Detection (HP)
|
100% |
5411
64.3 IPS |
|
|
Face Detection (Q)
|
97% |
5074
60.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
4159
32.0 IPS |
|
|
Depth Estimation (HP)
|
98% |
9547
73.8 IPS |
|
|
Depth Estimation (Q)
|
61% |
7425
72.3 IPS |
|
|
Style Transfer (SP)
|
100% |
10969
14.1 IPS |
|
|
Style Transfer (HP)
|
100% |
20905
26.9 IPS |
|
|
Style Transfer (Q)
|
98% |
20890
26.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2140
79.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
3484
128.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3418
126.7 IPS |
|
|
Text Classification (SP)
|
35% |
42
410.1 IPS |
|
|
Text Classification (HP)
|
35% |
44
396.7 IPS |
|
|
Text Classification (Q)
|
33% |
35
389.7 IPS |
|
|
Machine Translation (SP)
|
100% |
653
11.2 IPS |
|
|
Machine Translation (HP)
|
100% |
1080
18.6 IPS |
|
|
Machine Translation (Q)
|
48% |
394
15.1 IPS |