samsung SM-F966B
Geekbench AI Score
2494
Single Precision Score
3900
Half Precision Score
2874
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | August 12 2025 05:46 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| 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% |
1689
314.1 IPS |
|
|
Image Classification (HP)
|
100% |
2902
539.7 IPS |
|
|
Image Classification (Q)
|
100% |
2894
538.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
3173
51.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
5820
94.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
5078
82.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
13784
16.1 IPS |
|
|
Pose Estimation (HP)
|
99% |
24909
29.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
13442
15.8 IPS |
|
|
Object Detection (SP)
|
100% |
949
75.3 IPS |
|
|
Object Detection (HP)
|
99% |
1237
98.1 IPS |
|
|
Object Detection (Q)
|
85% |
1227
98.8 IPS |
|
|
Face Detection (SP)
|
100% |
3437
40.8 IPS |
|
|
Face Detection (HP)
|
100% |
5563
66.1 IPS |
|
|
Face Detection (Q)
|
97% |
4824
57.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
7045
54.3 IPS |
|
|
Depth Estimation (HP)
|
98% |
9664
74.7 IPS |
|
|
Depth Estimation (Q)
|
61% |
7419
72.3 IPS |
|
|
Style Transfer (SP)
|
100% |
17398
22.4 IPS |
|
|
Style Transfer (HP)
|
100% |
38176
49.1 IPS |
|
|
Style Transfer (Q)
|
98% |
37588
48.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3722
137.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5761
212.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
5633
208.8 IPS |
|
|
Text Classification (SP)
|
35% |
80
783.2 IPS |
|
|
Text Classification (HP)
|
35% |
83
755.9 IPS |
|
|
Text Classification (Q)
|
33% |
60
674.9 IPS |
|
|
Machine Translation (SP)
|
100% |
1060
18.3 IPS |
|
|
Machine Translation (HP)
|
100% |
1596
27.5 IPS |
|
|
Machine Translation (Q)
|
48% |
350
13.4 IPS |
