samsung SM-F966B
Geekbench AI Score
2745
Single Precision Score
2600
Half Precision Score
4548
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | August 12 2025 05:35 PM |
| Views | 6 |
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% |
2187
406.7 IPS |
|
|
Image Classification (HP)
|
100% |
2241
416.8 IPS |
|
|
Image Classification (Q)
|
100% |
4746
882.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
2602
42.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
2635
42.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
5725
93.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
5536
6.46 IPS |
|
|
Pose Estimation (HP)
|
100% |
4439
5.18 IPS |
|
|
Pose Estimation (Q)
|
84% |
11966
14.2 IPS |
|
|
Object Detection (SP)
|
98% |
1623
129.2 IPS |
|
|
Object Detection (HP)
|
98% |
1631
129.7 IPS |
|
|
Object Detection (Q)
|
83% |
3761
303.8 IPS |
|
|
Face Detection (SP)
|
100% |
4342
51.6 IPS |
|
|
Face Detection (HP)
|
100% |
4374
52.0 IPS |
|
|
Face Detection (Q)
|
95% |
8937
106.7 IPS |
|
|
Depth Estimation (SP)
|
99% |
4471
34.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
4107
31.7 IPS |
|
|
Depth Estimation (Q)
|
64% |
7856
72.0 IPS |
|
|
Style Transfer (SP)
|
89% |
10233
13.3 IPS |
|
|
Style Transfer (HP)
|
89% |
9904
12.9 IPS |
|
|
Style Transfer (Q)
|
98% |
17628
22.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1908
70.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2057
75.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
5245
194.4 IPS |
|
|
Text Classification (SP)
|
100% |
917
1.22 KIPS |
|
|
Text Classification (HP)
|
99% |
883
1.18 KIPS |
|
|
Text Classification (Q)
|
88% |
1013
1.37 KIPS |
|
|
Machine Translation (SP)
|
100% |
1367
23.5 IPS |
|
|
Machine Translation (HP)
|
100% |
1023
17.6 IPS |
|
|
Machine Translation (Q)
|
50% |
471
16.7 IPS |
