samsung SM-F966B
Geekbench AI Score
2216
Single Precision Score
3429
Half Precision Score
2952
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | epicgeek |
| Upload Date | November 25 2025 11:13 PM |
| Views | 11 |
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 | 10.85 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1701
316.3 IPS |
|
|
Image Classification (HP)
|
100% |
3052
567.6 IPS |
|
|
Image Classification (Q)
|
100% |
2627
488.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
3142
50.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
5604
90.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
5711
92.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
13832
16.1 IPS |
|
|
Pose Estimation (HP)
|
99% |
24646
28.8 IPS |
|
|
Pose Estimation (Q)
|
95% |
24481
28.7 IPS |
|
|
Object Detection (SP)
|
100% |
1115
88.4 IPS |
|
|
Object Detection (HP)
|
99% |
1411
111.9 IPS |
|
|
Object Detection (Q)
|
85% |
1193
96.1 IPS |
|
|
Face Detection (SP)
|
100% |
3827
45.5 IPS |
|
|
Face Detection (HP)
|
100% |
6724
79.9 IPS |
|
|
Face Detection (Q)
|
97% |
6270
74.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
4667
36.0 IPS |
|
|
Depth Estimation (HP)
|
98% |
6720
51.9 IPS |
|
|
Depth Estimation (Q)
|
61% |
5289
51.5 IPS |
|
|
Style Transfer (SP)
|
100% |
12646
16.3 IPS |
|
|
Style Transfer (HP)
|
100% |
26634
34.2 IPS |
|
|
Style Transfer (Q)
|
98% |
25191
32.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2589
95.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
4142
152.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
4022
149.0 IPS |
|
|
Text Classification (SP)
|
35% |
56
545.8 IPS |
|
|
Text Classification (HP)
|
35% |
63
576.0 IPS |
|
|
Text Classification (Q)
|
33% |
73
818.2 IPS |
|
|
Machine Translation (SP)
|
100% |
1061
18.3 IPS |
|
|
Machine Translation (HP)
|
100% |
1205
20.8 IPS |
|
|
Machine Translation (Q)
|
48% |
468
18.0 IPS |
