samsung SM-F966N
Geekbench AI Score
2348
Single Precision Score
2109
Half Precision Score
3635
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | September 03 2025 01:16 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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 | 10.85 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2111
392.6 IPS |
|
|
Image Classification (HP)
|
100% |
2028
377.1 IPS |
|
|
Image Classification (Q)
|
100% |
4547
845.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
2485
40.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
2354
38.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
4837
78.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
5194
6.06 IPS |
|
|
Pose Estimation (HP)
|
100% |
3917
4.57 IPS |
|
|
Pose Estimation (Q)
|
84% |
8982
10.7 IPS |
|
|
Object Detection (SP)
|
98% |
1193
94.9 IPS |
|
|
Object Detection (HP)
|
98% |
1214
96.6 IPS |
|
|
Object Detection (Q)
|
83% |
3057
246.9 IPS |
|
|
Face Detection (SP)
|
100% |
3751
44.6 IPS |
|
|
Face Detection (HP)
|
100% |
3959
47.0 IPS |
|
|
Face Detection (Q)
|
95% |
6301
75.2 IPS |
|
|
Depth Estimation (SP)
|
99% |
3714
28.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
3443
26.6 IPS |
|
|
Depth Estimation (Q)
|
64% |
6914
63.3 IPS |
|
|
Style Transfer (SP)
|
89% |
8518
11.1 IPS |
|
|
Style Transfer (HP)
|
89% |
7834
10.2 IPS |
|
|
Style Transfer (Q)
|
98% |
16224
20.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1702
62.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1717
63.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3965
146.9 IPS |
|
|
Text Classification (SP)
|
100% |
689
919.5 IPS |
|
|
Text Classification (HP)
|
99% |
404
539.5 IPS |
|
|
Text Classification (Q)
|
88% |
601
810.3 IPS |
|
|
Machine Translation (SP)
|
100% |
1129
19.4 IPS |
|
|
Machine Translation (HP)
|
100% |
1038
17.9 IPS |
|
|
Machine Translation (Q)
|
50% |
396
14.0 IPS |
