Samsung Galaxy Tab S7
Geekbench AI Score
293
Single Precision Score
444
Half Precision Score
452
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Cifra45 |
| Upload Date | December 28 2024 01:20 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Qualcomm Snapdragon 865 |
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Samsung Galaxy Tab S7 |
| Model ID | samsung SM-T875 |
| Motherboard | kona |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3341 revision 0 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.42 GHz |
| Cluster 3 | 1 Core @ 3.09 GHz |
| Memory Information | |
|---|---|
| Size | 5.52 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
285
53.0 IPS |
|
|
Image Classification (HP)
|
100% |
425
79.1 IPS |
|
|
Image Classification (Q)
|
97% |
422
78.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
181
2.94 IPS |
|
|
Image Segmentation (HP)
|
100% |
243
3.93 IPS |
|
|
Image Segmentation (Q)
|
98% |
235
3.82 IPS |
|
|
Pose Estimation (SP)
|
100% |
559
0.65 IPS |
|
|
Pose Estimation (HP)
|
100% |
1118
1.30 IPS |
|
|
Pose Estimation (Q)
|
95% |
1111
1.30 IPS |
|
|
Object Detection (SP)
|
100% |
216
17.1 IPS |
|
|
Object Detection (HP)
|
100% |
197
15.6 IPS |
|
|
Object Detection (Q)
|
89% |
205
16.4 IPS |
|
|
Face Detection (SP)
|
100% |
661
7.85 IPS |
|
|
Face Detection (HP)
|
100% |
1200
14.3 IPS |
|
|
Face Detection (Q)
|
97% |
1183
14.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
658
5.07 IPS |
|
|
Depth Estimation (HP)
|
99% |
1241
9.59 IPS |
|
|
Depth Estimation (Q)
|
62% |
1008
9.55 IPS |
|
|
Style Transfer (SP)
|
100% |
1258
1.62 IPS |
|
|
Style Transfer (HP)
|
100% |
3123
4.01 IPS |
|
|
Style Transfer (Q)
|
98% |
3099
4.00 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
299
11.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
616
22.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
592
21.9 IPS |
|
|
Text Classification (SP)
|
100% |
54
71.9 IPS |
|
|
Text Classification (HP)
|
100% |
54
71.6 IPS |
|
|
Text Classification (Q)
|
91% |
96
129.5 IPS |
|
|
Machine Translation (SP)
|
100% |
86
1.48 IPS |
|
|
Machine Translation (HP)
|
100% |
86
1.48 IPS |
|
|
Machine Translation (Q)
|
57% |
76
1.85 IPS |
