samsung SM-F966B
Geekbench AI Score
2684
Single Precision Score
2722
Half Precision Score
5006
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | August 29 2025 11:47 PM |
| Views | 4 |
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 | 10.85 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2109
392.2 IPS |
|
|
Image Classification (HP)
|
100% |
2159
401.5 IPS |
|
|
Image Classification (Q)
|
100% |
4543
844.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
2544
41.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
2543
41.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
5510
89.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
5431
6.34 IPS |
|
|
Pose Estimation (HP)
|
100% |
5158
6.02 IPS |
|
|
Pose Estimation (Q)
|
84% |
13825
16.4 IPS |
|
|
Object Detection (SP)
|
98% |
1318
104.9 IPS |
|
|
Object Detection (HP)
|
98% |
1555
123.7 IPS |
|
|
Object Detection (Q)
|
83% |
4007
323.7 IPS |
|
|
Face Detection (SP)
|
100% |
4211
50.0 IPS |
|
|
Face Detection (HP)
|
100% |
4436
52.7 IPS |
|
|
Face Detection (Q)
|
95% |
9844
117.5 IPS |
|
|
Depth Estimation (SP)
|
99% |
4657
36.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
4421
34.2 IPS |
|
|
Depth Estimation (Q)
|
64% |
8822
80.8 IPS |
|
|
Style Transfer (SP)
|
89% |
11047
14.3 IPS |
|
|
Style Transfer (HP)
|
89% |
10954
14.2 IPS |
|
|
Style Transfer (Q)
|
98% |
22486
29.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2170
80.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2231
82.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
6293
233.2 IPS |
|
|
Text Classification (SP)
|
100% |
807
1.08 KIPS |
|
|
Text Classification (HP)
|
99% |
967
1.29 KIPS |
|
|
Text Classification (Q)
|
88% |
1086
1.46 KIPS |
|
|
Machine Translation (SP)
|
100% |
1336
23.0 IPS |
|
|
Machine Translation (HP)
|
100% |
1098
18.9 IPS |
|
|
Machine Translation (Q)
|
50% |
535
19.0 IPS |
