samsung SM-F966B
Geekbench AI Score
515
Single Precision Score
493
Half Precision Score
1055
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | teknoseyir |
| Upload Date | August 02 2025 04:14 PM |
| Views | 9 |
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% |
428
79.6 IPS |
|
|
Image Classification (HP)
|
100% |
377
70.2 IPS |
|
|
Image Classification (Q)
|
99% |
730
136.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
406
6.59 IPS |
|
|
Image Segmentation (HP)
|
100% |
407
6.60 IPS |
|
|
Image Segmentation (Q)
|
98% |
775
12.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
540
0.63 IPS |
|
|
Pose Estimation (HP)
|
100% |
474
0.55 IPS |
|
|
Pose Estimation (Q)
|
98% |
1917
2.24 IPS |
|
|
Object Detection (SP)
|
100% |
266
21.1 IPS |
|
|
Object Detection (HP)
|
100% |
288
22.8 IPS |
|
|
Object Detection (Q)
|
87% |
774
62.1 IPS |
|
|
Face Detection (SP)
|
100% |
761
9.05 IPS |
|
|
Face Detection (HP)
|
100% |
711
8.45 IPS |
|
|
Face Detection (Q)
|
97% |
1440
17.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
616
4.75 IPS |
|
|
Depth Estimation (HP)
|
99% |
617
4.75 IPS |
|
|
Depth Estimation (Q)
|
64% |
1364
12.4 IPS |
|
|
Style Transfer (SP)
|
100% |
1056
1.36 IPS |
|
|
Style Transfer (HP)
|
100% |
1016
1.31 IPS |
|
|
Style Transfer (Q)
|
98% |
2662
3.43 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
302
11.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
308
11.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1091
40.4 IPS |
|
|
Text Classification (SP)
|
100% |
436
582.2 IPS |
|
|
Text Classification (HP)
|
100% |
437
582.8 IPS |
|
|
Text Classification (Q)
|
91% |
720
967.7 IPS |
|
|
Machine Translation (SP)
|
100% |
816
14.1 IPS |
|
|
Machine Translation (HP)
|
100% |
686
11.8 IPS |
|
|
Machine Translation (Q)
|
57% |
500
12.2 IPS |
