samsung SM-F966B
Geekbench AI Score
2849
Single Precision Score
4498
Half Precision Score
3540
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | Molpid |
| Upload Date | August 06 2025 09:21 PM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| 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% |
1958
364.1 IPS |
|
|
Image Classification (HP)
|
100% |
3557
661.5 IPS |
|
|
Image Classification (Q)
|
100% |
2087
388.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
3377
54.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
5587
90.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
5444
88.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
13902
16.2 IPS |
|
|
Pose Estimation (HP)
|
99% |
24864
29.0 IPS |
|
|
Pose Estimation (Q)
|
95% |
24124
28.3 IPS |
|
|
Object Detection (SP)
|
100% |
1487
117.9 IPS |
|
|
Object Detection (HP)
|
99% |
1916
152.0 IPS |
|
|
Object Detection (Q)
|
85% |
1911
153.8 IPS |
|
|
Face Detection (SP)
|
100% |
6253
74.3 IPS |
|
|
Face Detection (HP)
|
100% |
9559
113.6 IPS |
|
|
Face Detection (Q)
|
97% |
8624
102.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
7048
54.3 IPS |
|
|
Depth Estimation (HP)
|
98% |
8907
68.8 IPS |
|
|
Depth Estimation (Q)
|
61% |
7434
72.4 IPS |
|
|
Style Transfer (SP)
|
100% |
17200
22.1 IPS |
|
|
Style Transfer (HP)
|
100% |
38310
49.2 IPS |
|
|
Style Transfer (Q)
|
98% |
37917
48.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3724
137.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5795
214.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
5613
208.0 IPS |
|
|
Text Classification (SP)
|
35% |
87
849.7 IPS |
|
|
Text Classification (HP)
|
35% |
104
946.1 IPS |
|
|
Text Classification (Q)
|
33% |
69
774.7 IPS |
|
|
Machine Translation (SP)
|
100% |
1050
18.1 IPS |
|
|
Machine Translation (HP)
|
100% |
1823
31.4 IPS |
|
|
Machine Translation (Q)
|
48% |
628
24.1 IPS |
