samsung SM-F966U
Geekbench AI Score
1745
Single Precision Score
1685
Half Precision Score
2625
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | September 10 2025 07:55 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | samsung SM-F966U |
| Model ID | samsung SM-F966U |
| Motherboard | sun |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | Qualcomm ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 3 part 1 revision 4 |
| Base Frequency | 3.53 GHz |
| Cluster 1 | 6 Cores @ 3.53 GHz |
| Cluster 2 | 2 Cores @ 4.47 GHz |
| Memory Information | |
|---|---|
| Size | 10.85 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1172
217.9 IPS |
|
|
Image Classification (HP)
|
100% |
1107
205.9 IPS |
|
|
Image Classification (Q)
|
100% |
1126
209.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
1418
23.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
2037
33.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
4448
72.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
4151
4.84 IPS |
|
|
Pose Estimation (HP)
|
100% |
3153
3.68 IPS |
|
|
Pose Estimation (Q)
|
84% |
7244
8.59 IPS |
|
|
Object Detection (SP)
|
98% |
900
71.6 IPS |
|
|
Object Detection (HP)
|
98% |
1130
89.9 IPS |
|
|
Object Detection (Q)
|
83% |
2374
191.8 IPS |
|
|
Face Detection (SP)
|
100% |
3297
39.2 IPS |
|
|
Face Detection (HP)
|
100% |
3059
36.4 IPS |
|
|
Face Detection (Q)
|
95% |
6415
76.6 IPS |
|
|
Depth Estimation (SP)
|
99% |
3022
23.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
2727
21.1 IPS |
|
|
Depth Estimation (Q)
|
64% |
5365
49.1 IPS |
|
|
Style Transfer (SP)
|
89% |
7058
9.16 IPS |
|
|
Style Transfer (HP)
|
89% |
6510
8.45 IPS |
|
|
Style Transfer (Q)
|
98% |
13089
16.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1335
49.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1261
46.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3105
115.1 IPS |
|
|
Text Classification (SP)
|
100% |
638
852.0 IPS |
|
|
Text Classification (HP)
|
99% |
511
682.5 IPS |
|
|
Text Classification (Q)
|
88% |
434
585.7 IPS |
|
|
Machine Translation (SP)
|
100% |
705
12.1 IPS |
|
|
Machine Translation (HP)
|
100% |
660
11.4 IPS |
|
|
Machine Translation (Q)
|
50% |
298
10.6 IPS |
