samsung SM-F966B
Geekbench AI Score
2405
Single Precision Score
2418
Half Precision Score
4162
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | December 08 2025 04:27 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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 | 14.75 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1943
361.4 IPS |
|
|
Image Classification (HP)
|
100% |
1945
361.8 IPS |
|
|
Image Classification (Q)
|
100% |
4635
862.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
2316
37.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
2306
37.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
5074
82.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
5129
5.98 IPS |
|
|
Pose Estimation (HP)
|
100% |
4102
4.79 IPS |
|
|
Pose Estimation (Q)
|
84% |
10672
12.7 IPS |
|
|
Object Detection (SP)
|
98% |
1313
104.5 IPS |
|
|
Object Detection (HP)
|
98% |
1539
122.4 IPS |
|
|
Object Detection (Q)
|
83% |
3503
283.0 IPS |
|
|
Face Detection (SP)
|
100% |
4040
48.0 IPS |
|
|
Face Detection (HP)
|
100% |
4210
50.0 IPS |
|
|
Face Detection (Q)
|
95% |
7774
92.8 IPS |
|
|
Depth Estimation (SP)
|
99% |
3501
27.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
3625
28.0 IPS |
|
|
Depth Estimation (Q)
|
64% |
7161
65.6 IPS |
|
|
Style Transfer (SP)
|
89% |
10120
13.1 IPS |
|
|
Style Transfer (HP)
|
89% |
9069
11.8 IPS |
|
|
Style Transfer (Q)
|
98% |
16505
21.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1992
73.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1941
71.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
4535
168.0 IPS |
|
|
Text Classification (SP)
|
100% |
579
773.0 IPS |
|
|
Text Classification (HP)
|
99% |
910
1.21 KIPS |
|
|
Text Classification (Q)
|
88% |
932
1.26 KIPS |
|
|
Machine Translation (SP)
|
100% |
1298
22.4 IPS |
|
|
Machine Translation (HP)
|
100% |
990
17.1 IPS |
|
|
Machine Translation (Q)
|
50% |
457
16.2 IPS |
