samsung SM-F966B
Geekbench AI Score
2436
Single Precision Score
2666
Half Precision Score
4537
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| Upload Date | January 06 2026 12:00 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% |
2042
379.8 IPS |
|
|
Image Classification (HP)
|
100% |
2023
376.1 IPS |
|
|
Image Classification (Q)
|
100% |
4333
805.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
2353
38.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
2434
39.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
5432
88.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
5180
6.04 IPS |
|
|
Pose Estimation (HP)
|
100% |
4971
5.80 IPS |
|
|
Pose Estimation (Q)
|
84% |
10989
13.0 IPS |
|
|
Object Detection (SP)
|
98% |
1160
92.3 IPS |
|
|
Object Detection (HP)
|
98% |
1598
127.2 IPS |
|
|
Object Detection (Q)
|
83% |
3738
302.0 IPS |
|
|
Face Detection (SP)
|
100% |
4321
51.3 IPS |
|
|
Face Detection (HP)
|
100% |
4471
53.1 IPS |
|
|
Face Detection (Q)
|
95% |
9399
112.2 IPS |
|
|
Depth Estimation (SP)
|
99% |
4417
34.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
4309
33.3 IPS |
|
|
Depth Estimation (Q)
|
64% |
7943
72.7 IPS |
|
|
Style Transfer (SP)
|
89% |
9664
12.5 IPS |
|
|
Style Transfer (HP)
|
89% |
10768
14.0 IPS |
|
|
Style Transfer (Q)
|
98% |
18640
24.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1809
66.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2222
82.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
6213
230.2 IPS |
|
|
Text Classification (SP)
|
100% |
602
803.0 IPS |
|
|
Text Classification (HP)
|
99% |
930
1.24 KIPS |
|
|
Text Classification (Q)
|
88% |
1013
1.37 KIPS |
|
|
Machine Translation (SP)
|
100% |
1272
21.9 IPS |
|
|
Machine Translation (HP)
|
100% |
1085
18.7 IPS |
|
|
Machine Translation (Q)
|
50% |
437
15.5 IPS |
