samsung SM-F966N
Geekbench AI Score
2682
Single Precision Score
4185
Half Precision Score
3476
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | October 22 2025 03:20 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Qualcomm ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | samsung SM-F966N |
| Model ID | samsung SM-F966N |
| 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 | 10.75 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1596
296.7 IPS |
|
|
Image Classification (HP)
|
100% |
2289
425.8 IPS |
|
|
Image Classification (Q)
|
100% |
2080
386.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
3183
51.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
5983
97.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
5083
82.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
13836
16.1 IPS |
|
|
Pose Estimation (HP)
|
99% |
24631
28.7 IPS |
|
|
Pose Estimation (Q)
|
95% |
22676
26.6 IPS |
|
|
Object Detection (SP)
|
100% |
1474
116.9 IPS |
|
|
Object Detection (HP)
|
99% |
2018
160.0 IPS |
|
|
Object Detection (Q)
|
85% |
1821
146.6 IPS |
|
|
Face Detection (SP)
|
100% |
5457
64.8 IPS |
|
|
Face Detection (HP)
|
100% |
8824
104.9 IPS |
|
|
Face Detection (Q)
|
97% |
9263
110.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
7027
54.1 IPS |
|
|
Depth Estimation (HP)
|
98% |
9689
74.9 IPS |
|
|
Depth Estimation (Q)
|
61% |
7449
72.6 IPS |
|
|
Style Transfer (SP)
|
100% |
17296
22.2 IPS |
|
|
Style Transfer (HP)
|
100% |
37806
48.6 IPS |
|
|
Style Transfer (Q)
|
98% |
34015
43.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3406
125.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5704
210.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
5668
210.1 IPS |
|
|
Text Classification (SP)
|
35% |
75
725.9 IPS |
|
|
Text Classification (HP)
|
35% |
78
709.0 IPS |
|
|
Text Classification (Q)
|
33% |
66
740.1 IPS |
|
|
Machine Translation (SP)
|
100% |
1101
19.0 IPS |
|
|
Machine Translation (HP)
|
100% |
1685
29.0 IPS |
|
|
Machine Translation (Q)
|
48% |
672
25.8 IPS |
