Samsung Galaxy Tab S9
Geekbench AI Score
280
Single Precision Score
281
Half Precision Score
636
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | angelpradomx |
| Upload Date | June 01 2025 03:40 AM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Qualcomm Snapdragon 8 Gen 2 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | Samsung Galaxy Tab S9 |
| Model ID | samsung SM-X710 |
| Motherboard | kalama |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3406 revision 0 |
| Base Frequency | 2.02 GHz |
| Cluster 1 | 3 Cores @ 2.02 GHz |
| Cluster 2 | 4 Cores @ 2.80 GHz |
| Cluster 3 | 1 Core @ 3.36 GHz |
| Memory Information | |
|---|---|
| Size | 10.92 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
160
29.8 IPS |
|
|
Image Classification (HP)
|
100% |
161
29.9 IPS |
|
|
Image Classification (Q)
|
99% |
416
77.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
213
3.46 IPS |
|
|
Image Segmentation (HP)
|
100% |
214
3.47 IPS |
|
|
Image Segmentation (Q)
|
98% |
442
7.19 IPS |
|
|
Pose Estimation (SP)
|
100% |
289
0.34 IPS |
|
|
Pose Estimation (HP)
|
100% |
290
0.34 IPS |
|
|
Pose Estimation (Q)
|
98% |
1096
1.28 IPS |
|
|
Object Detection (SP)
|
100% |
159
12.6 IPS |
|
|
Object Detection (HP)
|
100% |
159
12.7 IPS |
|
|
Object Detection (Q)
|
87% |
451
36.2 IPS |
|
|
Face Detection (SP)
|
100% |
455
5.41 IPS |
|
|
Face Detection (HP)
|
100% |
456
5.42 IPS |
|
|
Face Detection (Q)
|
97% |
941
11.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
381
2.94 IPS |
|
|
Depth Estimation (HP)
|
99% |
381
2.94 IPS |
|
|
Depth Estimation (Q)
|
64% |
885
8.03 IPS |
|
|
Style Transfer (SP)
|
100% |
685
0.88 IPS |
|
|
Style Transfer (HP)
|
100% |
682
0.88 IPS |
|
|
Style Transfer (Q)
|
98% |
1898
2.45 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
182
6.72 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
183
6.75 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
634
23.5 IPS |
|
|
Text Classification (SP)
|
100% |
223
297.7 IPS |
|
|
Text Classification (HP)
|
100% |
224
298.8 IPS |
|
|
Text Classification (Q)
|
91% |
373
500.9 IPS |
|
|
Machine Translation (SP)
|
100% |
397
6.84 IPS |
|
|
Machine Translation (HP)
|
100% |
400
6.89 IPS |
|
|
Machine Translation (Q)
|
57% |
320
7.83 IPS |
