Samsung Galaxy Tab S9
Geekbench AI Score
911
Single Precision Score
908
Half Precision Score
1638
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | angelpradomx |
| Upload Date | June 01 2025 03:18 AM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
957
178.0 IPS |
|
|
Image Classification (HP)
|
100% |
694
129.1 IPS |
|
|
Image Classification (Q)
|
100% |
1491
277.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
531
8.62 IPS |
|
|
Image Segmentation (HP)
|
100% |
772
12.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
1711
27.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
2047
2.39 IPS |
|
|
Pose Estimation (HP)
|
100% |
1448
1.69 IPS |
|
|
Pose Estimation (Q)
|
84% |
2879
3.41 IPS |
|
|
Object Detection (SP)
|
98% |
563
44.8 IPS |
|
|
Object Detection (HP)
|
98% |
532
42.3 IPS |
|
|
Object Detection (Q)
|
83% |
946
76.5 IPS |
|
|
Face Detection (SP)
|
100% |
971
11.5 IPS |
|
|
Face Detection (HP)
|
100% |
1217
14.5 IPS |
|
|
Face Detection (Q)
|
95% |
2122
25.3 IPS |
|
|
Depth Estimation (SP)
|
99% |
1095
8.46 IPS |
|
|
Depth Estimation (HP)
|
99% |
1065
8.23 IPS |
|
|
Depth Estimation (Q)
|
64% |
2297
21.0 IPS |
|
|
Style Transfer (SP)
|
89% |
3403
4.42 IPS |
|
|
Style Transfer (HP)
|
89% |
3517
4.57 IPS |
|
|
Style Transfer (Q)
|
98% |
7116
9.18 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
648
23.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
900
33.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1948
72.2 IPS |
|
|
Text Classification (SP)
|
100% |
329
439.1 IPS |
|
|
Text Classification (HP)
|
99% |
301
401.8 IPS |
|
|
Text Classification (Q)
|
88% |
717
967.5 IPS |
|
|
Machine Translation (SP)
|
100% |
874
15.1 IPS |
|
|
Machine Translation (HP)
|
100% |
754
13.0 IPS |
|
|
Machine Translation (Q)
|
50% |
415
14.7 IPS |
