samsung SM-F966U1
Geekbench AI Score
2574
Single Precision Score
2410
Half Precision Score
4167
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | Billfumo |
| Upload Date | September 08 2025 09:07 PM |
| Views | 10 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | samsung SM-F966U1 |
| Model ID | samsung SM-F966U1 |
| 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% |
2160
401.7 IPS |
|
|
Image Classification (HP)
|
100% |
2186
406.6 IPS |
|
|
Image Classification (Q)
|
100% |
4611
857.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
2498
40.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
2344
38.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
5319
86.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
5390
6.29 IPS |
|
|
Pose Estimation (HP)
|
100% |
4296
5.01 IPS |
|
|
Pose Estimation (Q)
|
84% |
11104
13.2 IPS |
|
|
Object Detection (SP)
|
98% |
1321
105.1 IPS |
|
|
Object Detection (HP)
|
98% |
1421
113.1 IPS |
|
|
Object Detection (Q)
|
83% |
3600
290.8 IPS |
|
|
Face Detection (SP)
|
100% |
4307
51.2 IPS |
|
|
Face Detection (HP)
|
100% |
4279
50.8 IPS |
|
|
Face Detection (Q)
|
95% |
8784
104.9 IPS |
|
|
Depth Estimation (SP)
|
99% |
4179
32.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
3899
30.1 IPS |
|
|
Depth Estimation (Q)
|
64% |
7582
69.4 IPS |
|
|
Style Transfer (SP)
|
89% |
9883
12.8 IPS |
|
|
Style Transfer (HP)
|
89% |
9441
12.3 IPS |
|
|
Style Transfer (Q)
|
98% |
16946
21.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1906
70.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2188
80.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
5085
188.4 IPS |
|
|
Text Classification (SP)
|
100% |
836
1.12 KIPS |
|
|
Text Classification (HP)
|
99% |
579
773.1 IPS |
|
|
Text Classification (Q)
|
88% |
641
863.9 IPS |
|
|
Machine Translation (SP)
|
100% |
1175
20.2 IPS |
|
|
Machine Translation (HP)
|
100% |
1063
18.3 IPS |
|
|
Machine Translation (Q)
|
50% |
438
15.5 IPS |
