samsung SM-F741U
Geekbench AI Score
957
Single Precision Score
1394
Half Precision Score
1301
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| Upload Date | September 18 2024 10:09 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-F741U |
| Model ID | samsung SM-F741U |
| Motherboard | pineapple |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.26 GHz |
| Cluster 1 | 2 Cores @ 2.27 GHz |
| Cluster 2 | 2 Cores @ 2.96 GHz |
| Cluster 3 | 3 Cores @ 3.15 GHz |
| Cluster 4 | 1 Core @ 3.40 GHz |
| Memory Information | |
|---|---|
| Size | 10.86 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
560
104.2 IPS |
|
|
Image Classification (HP)
|
100% |
501
93.1 IPS |
|
|
Image Classification (Q)
|
96% |
477
89.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
999
16.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
1453
23.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
1145
18.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
1069
1.25 IPS |
|
|
Pose Estimation (HP)
|
100% |
2163
2.52 IPS |
|
|
Pose Estimation (Q)
|
96% |
1988
2.33 IPS |
|
|
Object Detection (SP)
|
100% |
579
45.9 IPS |
|
|
Object Detection (HP)
|
100% |
703
55.7 IPS |
|
|
Object Detection (Q)
|
87% |
677
54.4 IPS |
|
|
Face Detection (SP)
|
100% |
2017
24.0 IPS |
|
|
Face Detection (HP)
|
100% |
3182
37.8 IPS |
|
|
Face Detection (Q)
|
97% |
2252
26.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
1456
11.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
2877
22.2 IPS |
|
|
Depth Estimation (Q)
|
63% |
2375
22.0 IPS |
|
|
Style Transfer (SP)
|
100% |
4934
6.34 IPS |
|
|
Style Transfer (HP)
|
100% |
8228
10.6 IPS |
|
|
Style Transfer (Q)
|
98% |
8027
10.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
412
15.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1081
39.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1056
39.1 IPS |
|
|
Text Classification (SP)
|
100% |
450
600.7 IPS |
|
|
Text Classification (HP)
|
100% |
450
600.1 IPS |
|
|
Text Classification (Q)
|
91% |
727
977.5 IPS |
|
|
Machine Translation (SP)
|
100% |
699
12.0 IPS |
|
|
Machine Translation (HP)
|
100% |
687
11.8 IPS |
|
|
Machine Translation (Q)
|
57% |
576
14.1 IPS |
