samsung SM-F966B
Geekbench AI Score
2609
Single Precision Score
4142
Half Precision Score
3525
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | teknoseyir |
| Upload Date | August 02 2025 04:04 PM |
| Views | 10 |
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% |
1771
329.4 IPS |
|
|
Image Classification (HP)
|
100% |
2929
544.7 IPS |
|
|
Image Classification (Q)
|
100% |
3436
639.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
3434
55.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
5619
91.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
5525
89.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
12877
15.0 IPS |
|
|
Pose Estimation (HP)
|
99% |
22254
26.0 IPS |
|
|
Pose Estimation (Q)
|
95% |
20461
24.0 IPS |
|
|
Object Detection (SP)
|
100% |
1370
108.7 IPS |
|
|
Object Detection (HP)
|
99% |
1801
142.8 IPS |
|
|
Object Detection (Q)
|
85% |
1722
138.6 IPS |
|
|
Face Detection (SP)
|
100% |
5158
61.3 IPS |
|
|
Face Detection (HP)
|
100% |
10354
123.0 IPS |
|
|
Face Detection (Q)
|
97% |
8186
97.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
6435
49.6 IPS |
|
|
Depth Estimation (HP)
|
98% |
8824
68.2 IPS |
|
|
Depth Estimation (Q)
|
61% |
6855
66.8 IPS |
|
|
Style Transfer (SP)
|
100% |
15399
19.8 IPS |
|
|
Style Transfer (HP)
|
100% |
32543
41.8 IPS |
|
|
Style Transfer (Q)
|
98% |
34504
44.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3235
119.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5350
197.6 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
5019
186.0 IPS |
|
|
Text Classification (SP)
|
35% |
83
807.2 IPS |
|
|
Text Classification (HP)
|
35% |
89
807.8 IPS |
|
|
Text Classification (Q)
|
33% |
72
806.0 IPS |
|
|
Machine Translation (SP)
|
100% |
995
17.1 IPS |
|
|
Machine Translation (HP)
|
100% |
1592
27.4 IPS |
|
|
Machine Translation (Q)
|
48% |
634
24.3 IPS |
