Samsung Galaxy Tab S9
Geekbench AI Score
844
Single Precision Score
1164
Half Precision Score
1116
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 01 2025 03:25 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| 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% |
661
122.9 IPS |
|
|
Image Classification (HP)
|
100% |
853
158.7 IPS |
|
|
Image Classification (Q)
|
96% |
806
150.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
1141
18.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
1909
30.9 IPS |
|
|
Image Segmentation (Q)
|
98% |
1280
20.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
954
1.11 IPS |
|
|
Pose Estimation (HP)
|
100% |
1442
1.68 IPS |
|
|
Pose Estimation (Q)
|
96% |
1434
1.68 IPS |
|
|
Object Detection (SP)
|
100% |
498
39.5 IPS |
|
|
Object Detection (HP)
|
100% |
778
61.7 IPS |
|
|
Object Detection (Q)
|
87% |
839
67.4 IPS |
|
|
Face Detection (SP)
|
100% |
2222
26.4 IPS |
|
|
Face Detection (HP)
|
100% |
3014
35.8 IPS |
|
|
Face Detection (Q)
|
97% |
2621
31.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
1520
11.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
2928
22.6 IPS |
|
|
Depth Estimation (Q)
|
63% |
2392
22.2 IPS |
|
|
Style Transfer (SP)
|
100% |
3864
4.97 IPS |
|
|
Style Transfer (HP)
|
100% |
8704
11.2 IPS |
|
|
Style Transfer (Q)
|
98% |
8644
11.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
443
16.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
366
13.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
374
13.9 IPS |
|
|
Text Classification (SP)
|
100% |
224
298.4 IPS |
|
|
Text Classification (HP)
|
100% |
223
298.0 IPS |
|
|
Text Classification (Q)
|
91% |
372
500.3 IPS |
|
|
Machine Translation (SP)
|
100% |
397
6.84 IPS |
|
|
Machine Translation (HP)
|
100% |
400
6.89 IPS |
|
|
Machine Translation (Q)
|
57% |
322
7.86 IPS |
