samsung SM-F966B
Geekbench AI Score
538
Single Precision Score
518
Half Precision Score
1117
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | teknoseyir |
| Upload Date | September 18 2025 04:37 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Qualcomm ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | samsung SM-F966B |
| Model ID | samsung SM-F966B |
| 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% |
424
78.8 IPS |
|
|
Image Classification (HP)
|
100% |
405
75.3 IPS |
|
|
Image Classification (Q)
|
99% |
721
134.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
401
6.51 IPS |
|
|
Image Segmentation (HP)
|
100% |
404
6.54 IPS |
|
|
Image Segmentation (Q)
|
98% |
822
13.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
539
0.63 IPS |
|
|
Pose Estimation (HP)
|
100% |
486
0.57 IPS |
|
|
Pose Estimation (Q)
|
98% |
1964
2.30 IPS |
|
|
Object Detection (SP)
|
100% |
296
23.5 IPS |
|
|
Object Detection (HP)
|
100% |
283
22.4 IPS |
|
|
Object Detection (Q)
|
87% |
780
62.5 IPS |
|
|
Face Detection (SP)
|
100% |
792
9.42 IPS |
|
|
Face Detection (HP)
|
100% |
750
8.91 IPS |
|
|
Face Detection (Q)
|
97% |
1560
18.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
659
5.08 IPS |
|
|
Depth Estimation (HP)
|
99% |
615
4.74 IPS |
|
|
Depth Estimation (Q)
|
64% |
1335
12.1 IPS |
|
|
Style Transfer (SP)
|
100% |
1061
1.36 IPS |
|
|
Style Transfer (HP)
|
100% |
1018
1.31 IPS |
|
|
Style Transfer (Q)
|
98% |
3136
4.04 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
331
12.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
362
13.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1288
47.7 IPS |
|
|
Text Classification (SP)
|
100% |
465
620.5 IPS |
|
|
Text Classification (HP)
|
100% |
504
673.1 IPS |
|
|
Text Classification (Q)
|
91% |
775
1.04 KIPS |
|
|
Machine Translation (SP)
|
100% |
880
15.2 IPS |
|
|
Machine Translation (HP)
|
100% |
732
12.6 IPS |
|
|
Machine Translation (Q)
|
57% |
515
12.6 IPS |
