samsung SM-F966B
Geekbench AI Score
2401
Single Precision Score
3621
Half Precision Score
3127
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | teknoseyir |
| Upload Date | August 02 2025 12:45 PM |
| Views | 5 |
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% |
1802
335.1 IPS |
|
|
Image Classification (HP)
|
100% |
3325
618.4 IPS |
|
|
Image Classification (Q)
|
100% |
2987
555.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
3673
59.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
5582
90.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
5669
92.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
13820
16.1 IPS |
|
|
Pose Estimation (HP)
|
99% |
24722
28.8 IPS |
|
|
Pose Estimation (Q)
|
95% |
24458
28.7 IPS |
|
|
Object Detection (SP)
|
100% |
996
79.0 IPS |
|
|
Object Detection (HP)
|
99% |
1446
114.7 IPS |
|
|
Object Detection (Q)
|
85% |
1420
114.3 IPS |
|
|
Face Detection (SP)
|
100% |
4238
50.4 IPS |
|
|
Face Detection (HP)
|
100% |
7261
86.3 IPS |
|
|
Face Detection (Q)
|
97% |
9223
110.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
7101
54.7 IPS |
|
|
Depth Estimation (HP)
|
98% |
9722
75.1 IPS |
|
|
Depth Estimation (Q)
|
61% |
7514
73.2 IPS |
|
|
Style Transfer (SP)
|
100% |
17056
21.9 IPS |
|
|
Style Transfer (HP)
|
100% |
38382
49.3 IPS |
|
|
Style Transfer (Q)
|
98% |
21014
27.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2304
85.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
3742
138.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3682
136.5 IPS |
|
|
Text Classification (SP)
|
35% |
54
524.7 IPS |
|
|
Text Classification (HP)
|
35% |
54
492.5 IPS |
|
|
Text Classification (Q)
|
33% |
66
733.6 IPS |
|
|
Machine Translation (SP)
|
100% |
1097
18.9 IPS |
|
|
Machine Translation (HP)
|
100% |
1069
18.4 IPS |
|
|
Machine Translation (Q)
|
48% |
430
16.5 IPS |
