User | VenomF5 |
Upload Date | July 25 2025 12:50 AM |
Views | 6 |
AI Information | |
---|---|
Framework | TensorFlow Lite |
Backend | GPU |
Device | Qualcomm Snapdragon 8 Gen 1 |
System Information | |
---|---|
Operating System | Android 15 |
Model | Samsung Galaxy S22 Ultra |
Model ID | samsung SM-S908U1 |
Motherboard | taro |
Governor | walt |
CPU Information | |
---|---|
Name | ARM ARMv8 |
Topology | 1 Processor, 8 Cores |
Identifier | ARM implementer 65 architecture 8 variant 2 part 3400 revision 0 |
Base Frequency | 1.78 GHz |
Cluster 1 | 4 Cores @ 1.79 GHz |
Cluster 2 | 3 Cores @ 2.50 GHz |
Cluster 3 | 1 Core @ 3.00 GHz |
Memory Information | |
---|---|
Size | 10.94 GB |
Workload | Accuracy | Score | |
---|---|---|---|
Image Classification (SP)
|
100% |
196
36.5 IPS |
|
Image Classification (HP)
|
100% |
331
61.5 IPS |
|
Image Classification (Q)
|
97% |
305
57.0 IPS |
|
Image Segmentation (SP)
|
100% |
395
6.41 IPS |
|
Image Segmentation (HP)
|
100% |
676
11.0 IPS |
|
Image Segmentation (Q)
|
98% |
656
10.7 IPS |
|
Pose Estimation (SP)
|
100% |
715
0.83 IPS |
|
Pose Estimation (HP)
|
100% |
1271
1.48 IPS |
|
Pose Estimation (Q)
|
95% |
1265
1.48 IPS |
|
Object Detection (SP)
|
100% |
375
29.8 IPS |
|
Object Detection (HP)
|
100% |
505
40.1 IPS |
|
Object Detection (Q)
|
89% |
548
43.9 IPS |
|
Face Detection (SP)
|
100% |
1530
18.2 IPS |
|
Face Detection (HP)
|
100% |
1459
17.3 IPS |
|
Face Detection (Q)
|
97% |
1370
16.3 IPS |
|
Depth Estimation (SP)
|
100% |
1093
8.42 IPS |
|
Depth Estimation (HP)
|
99% |
2218
17.1 IPS |
|
Depth Estimation (Q)
|
63% |
1969
18.5 IPS |
|
Style Transfer (SP)
|
100% |
2696
3.47 IPS |
|
Style Transfer (HP)
|
100% |
5570
7.16 IPS |
|
Style Transfer (Q)
|
98% |
5464
7.05 IPS |
|
Image Super-Resolution (SP)
|
100% |
363
13.4 IPS |
|
Image Super-Resolution (HP)
|
100% |
475
17.5 IPS |
|
Image Super-Resolution (Q)
|
97% |
473
17.5 IPS |
|
Text Classification (SP)
|
100% |
201
267.7 IPS |
|
Text Classification (HP)
|
100% |
201
267.6 IPS |
|
Text Classification (Q)
|
91% |
356
478.9 IPS |
|
Machine Translation (SP)
|
100% |
332
5.72 IPS |
|
Machine Translation (HP)
|
100% |
331
5.70 IPS |
|
Machine Translation (Q)
|
57% |
304
7.43 IPS |