samsung SM-F966N
Geekbench AI Score
2694
Single Precision Score
2673
Half Precision Score
4600
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | November 15 2025 02:44 PM |
| Views | 2 |
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 | 14.75 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2166
402.8 IPS |
|
|
Image Classification (HP)
|
100% |
2135
397.0 IPS |
|
|
Image Classification (Q)
|
100% |
4331
805.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
2400
38.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
2463
39.9 IPS |
|
|
Image Segmentation (Q)
|
98% |
5465
88.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
5258
6.14 IPS |
|
|
Pose Estimation (HP)
|
100% |
5050
5.89 IPS |
|
|
Pose Estimation (Q)
|
84% |
10719
12.7 IPS |
|
|
Object Detection (SP)
|
98% |
1389
110.5 IPS |
|
|
Object Detection (HP)
|
98% |
1601
127.4 IPS |
|
|
Object Detection (Q)
|
83% |
3685
297.7 IPS |
|
|
Face Detection (SP)
|
100% |
4374
52.0 IPS |
|
|
Face Detection (HP)
|
100% |
4200
49.9 IPS |
|
|
Face Detection (Q)
|
95% |
9327
111.4 IPS |
|
|
Depth Estimation (SP)
|
99% |
4580
35.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
4492
34.7 IPS |
|
|
Depth Estimation (Q)
|
64% |
9084
83.2 IPS |
|
|
Style Transfer (SP)
|
89% |
11020
14.3 IPS |
|
|
Style Transfer (HP)
|
89% |
10089
13.1 IPS |
|
|
Style Transfer (Q)
|
98% |
21373
27.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2240
82.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2155
79.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
5097
188.9 IPS |
|
|
Text Classification (SP)
|
100% |
800
1.07 KIPS |
|
|
Text Classification (HP)
|
99% |
954
1.27 KIPS |
|
|
Text Classification (Q)
|
88% |
1048
1.41 KIPS |
|
|
Machine Translation (SP)
|
100% |
1341
23.1 IPS |
|
|
Machine Translation (HP)
|
100% |
1121
19.3 IPS |
|
|
Machine Translation (Q)
|
50% |
470
16.7 IPS |
