Samsung Galaxy Tab S9
Geekbench AI Score
979
Single Precision Score
903
Half Precision Score
1611
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | December 25 2024 05:46 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm Snapdragon 8 Gen 2 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| 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 | 7.03 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1377
256.1 IPS |
|
|
Image Classification (HP)
|
100% |
732
136.1 IPS |
|
|
Image Classification (Q)
|
100% |
2061
383.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
457
7.40 IPS |
|
|
Image Segmentation (HP)
|
100% |
507
8.22 IPS |
|
|
Image Segmentation (Q)
|
98% |
2252
36.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
2921
3.41 IPS |
|
|
Pose Estimation (HP)
|
100% |
1679
1.96 IPS |
|
|
Pose Estimation (Q)
|
84% |
6037
7.16 IPS |
|
|
Object Detection (SP)
|
98% |
302
24.0 IPS |
|
|
Object Detection (HP)
|
98% |
830
66.0 IPS |
|
|
Object Detection (Q)
|
83% |
1031
83.3 IPS |
|
|
Face Detection (SP)
|
100% |
2347
27.9 IPS |
|
|
Face Detection (HP)
|
100% |
1740
20.7 IPS |
|
|
Face Detection (Q)
|
95% |
1600
19.1 IPS |
|
|
Depth Estimation (SP)
|
99% |
1214
9.38 IPS |
|
|
Depth Estimation (HP)
|
99% |
1053
8.14 IPS |
|
|
Depth Estimation (Q)
|
64% |
1819
16.7 IPS |
|
|
Style Transfer (SP)
|
89% |
3177
4.12 IPS |
|
|
Style Transfer (HP)
|
89% |
2362
3.07 IPS |
|
|
Style Transfer (Q)
|
98% |
4619
5.96 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
569
21.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
811
30.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1465
54.3 IPS |
|
|
Text Classification (SP)
|
100% |
323
431.1 IPS |
|
|
Text Classification (HP)
|
99% |
239
318.6 IPS |
|
|
Text Classification (Q)
|
88% |
549
740.7 IPS |
|
|
Machine Translation (SP)
|
100% |
882
15.2 IPS |
|
|
Machine Translation (HP)
|
100% |
839
14.5 IPS |
|
|
Machine Translation (Q)
|
50% |
378
13.4 IPS |
