| User | harsidh |
| Upload Date | September 26 2025 05:38 AM |
| Views | 4 |
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | samsung SM-S721B |
| Model ID | samsung SM-S721B |
| Motherboard | s5e9945 |
| Governor | energy_aware |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 10 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 1.96 GHz |
| Cluster 1 | 4 Cores @ 1.96 GHz |
| Cluster 2 | 3 Cores @ 2.59 GHz |
| Cluster 3 | 2 Cores @ 2.90 GHz |
| Cluster 4 | 1 Core @ 3.11 GHz |
| Memory Information | |
|---|---|
| Size | 7.06 GB |
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
783
145.7 IPS |
|
|
Image Classification (HP)
|
100% |
1265
235.3 IPS |
|
|
Image Classification (Q)
|
100% |
1157
215.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
1391
22.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
2501
40.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
2350
38.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
6289
7.34 IPS |
|
|
Pose Estimation (HP)
|
99% |
13168
15.4 IPS |
|
|
Pose Estimation (Q)
|
95% |
11662
13.7 IPS |
|
|
Object Detection (SP)
|
100% |
495
39.3 IPS |
|
|
Object Detection (HP)
|
99% |
892
70.7 IPS |
|
|
Object Detection (Q)
|
84% |
870
70.2 IPS |
|
|
Face Detection (SP)
|
100% |
2416
28.7 IPS |
|
|
Face Detection (HP)
|
100% |
4107
48.8 IPS |
|
|
Face Detection (Q)
|
97% |
4049
48.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
2864
22.1 IPS |
|
|
Depth Estimation (HP)
|
98% |
5255
40.6 IPS |
|
|
Depth Estimation (Q)
|
62% |
4541
43.8 IPS |
|
|
Style Transfer (SP)
|
100% |
12626
16.2 IPS |
|
|
Style Transfer (HP)
|
100% |
23988
30.8 IPS |
|
|
Style Transfer (Q)
|
98% |
24133
31.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1739
64.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
3259
120.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3383
125.4 IPS |
|
|
Text Classification (SP)
|
29% |
24
412.8 IPS |
|
|
Text Classification (HP)
|
35% |
62
559.5 IPS |
|
|
Text Classification (Q)
|
30% |
35
563.1 IPS |
|
|
Machine Translation (SP)
|
100% |
684
11.8 IPS |
|
|
Machine Translation (HP)
|
100% |
957
16.5 IPS |
|
|
Machine Translation (Q)
|
42% |
189
12.3 IPS |