samsung SM-F966B
Geekbench AI Score
2537
Single Precision Score
2590
Half Precision Score
4306
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | August 26 2025 09:00 PM |
| Views | 3 |
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% |
1942
361.1 IPS |
|
|
Image Classification (HP)
|
100% |
2013
374.4 IPS |
|
|
Image Classification (Q)
|
100% |
4508
838.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
2485
40.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
2400
38.9 IPS |
|
|
Image Segmentation (Q)
|
98% |
4994
81.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
5078
5.93 IPS |
|
|
Pose Estimation (HP)
|
100% |
4696
5.48 IPS |
|
|
Pose Estimation (Q)
|
84% |
9723
11.5 IPS |
|
|
Object Detection (SP)
|
98% |
1195
95.1 IPS |
|
|
Object Detection (HP)
|
98% |
1607
127.9 IPS |
|
|
Object Detection (Q)
|
83% |
3694
298.4 IPS |
|
|
Face Detection (SP)
|
100% |
4370
51.9 IPS |
|
|
Face Detection (HP)
|
100% |
4286
50.9 IPS |
|
|
Face Detection (Q)
|
95% |
9083
108.4 IPS |
|
|
Depth Estimation (SP)
|
99% |
3301
25.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
3813
29.5 IPS |
|
|
Depth Estimation (Q)
|
64% |
7031
64.4 IPS |
|
|
Style Transfer (SP)
|
89% |
11335
14.7 IPS |
|
|
Style Transfer (HP)
|
89% |
10057
13.1 IPS |
|
|
Style Transfer (Q)
|
98% |
16493
21.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1889
69.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2170
80.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
5194
192.5 IPS |
|
|
Text Classification (SP)
|
100% |
929
1.24 KIPS |
|
|
Text Classification (HP)
|
99% |
937
1.25 KIPS |
|
|
Text Classification (Q)
|
88% |
1002
1.35 KIPS |
|
|
Machine Translation (SP)
|
100% |
1319
22.7 IPS |
|
|
Machine Translation (HP)
|
100% |
1115
19.2 IPS |
|
|
Machine Translation (Q)
|
50% |
495
17.6 IPS |
