Samsung Galaxy Tab S7 FE
Geekbench AI Score
596
Single Precision Score
977
Half Precision Score
894
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | csoltenborn |
| Upload Date | November 29 2025 03:18 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Qualcomm Snapdragon 778G |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy Tab S7 FE |
| Model ID | samsung SM-T733 |
| Motherboard | lahaina |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 1 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 4 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 3.31 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
425
79.0 IPS |
|
|
Image Classification (HP)
|
100% |
662
123.0 IPS |
|
|
Image Classification (Q)
|
99% |
616
114.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
668
10.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
1152
18.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
1061
17.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
2287
2.67 IPS |
|
|
Pose Estimation (HP)
|
99% |
4139
4.83 IPS |
|
|
Pose Estimation (Q)
|
97% |
4075
4.77 IPS |
|
|
Object Detection (SP)
|
100% |
388
30.8 IPS |
|
|
Object Detection (HP)
|
99% |
612
48.5 IPS |
|
|
Object Detection (Q)
|
85% |
581
46.7 IPS |
|
|
Face Detection (SP)
|
100% |
1212
14.4 IPS |
|
|
Face Detection (HP)
|
100% |
2215
26.3 IPS |
|
|
Face Detection (Q)
|
97% |
1873
22.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
1423
11.0 IPS |
|
|
Depth Estimation (HP)
|
98% |
2405
18.6 IPS |
|
|
Depth Estimation (Q)
|
65% |
1991
17.9 IPS |
|
|
Style Transfer (SP)
|
100% |
2850
3.66 IPS |
|
|
Style Transfer (HP)
|
100% |
6072
7.81 IPS |
|
|
Style Transfer (Q)
|
98% |
6015
7.76 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
644
23.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1077
39.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1058
39.2 IPS |
|
|
Text Classification (SP)
|
35% |
24
231.4 IPS |
|
|
Text Classification (HP)
|
35% |
34
309.5 IPS |
|
|
Text Classification (Q)
|
35% |
33
304.1 IPS |
|
|
Machine Translation (SP)
|
100% |
299
5.15 IPS |
|
|
Machine Translation (HP)
|
97% |
347
6.00 IPS |
|
|
Machine Translation (Q)
|
64% |
270
5.54 IPS |
