samsung SM-F966B
Geekbench AI Score
464
Single Precision Score
443
Half Precision Score
944
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | teknoseyir |
| Upload Date | August 02 2025 12:56 PM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| 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% |
436
81.1 IPS |
|
|
Image Classification (HP)
|
100% |
432
80.4 IPS |
|
|
Image Classification (Q)
|
99% |
676
126.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
389
6.31 IPS |
|
|
Image Segmentation (HP)
|
100% |
397
6.43 IPS |
|
|
Image Segmentation (Q)
|
98% |
724
11.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
476
0.55 IPS |
|
|
Pose Estimation (HP)
|
100% |
382
0.45 IPS |
|
|
Pose Estimation (Q)
|
98% |
1707
2.00 IPS |
|
|
Object Detection (SP)
|
100% |
243
19.3 IPS |
|
|
Object Detection (HP)
|
100% |
245
19.4 IPS |
|
|
Object Detection (Q)
|
87% |
626
50.2 IPS |
|
|
Face Detection (SP)
|
100% |
649
7.71 IPS |
|
|
Face Detection (HP)
|
100% |
632
7.51 IPS |
|
|
Face Detection (Q)
|
97% |
1247
14.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
566
4.36 IPS |
|
|
Depth Estimation (HP)
|
99% |
494
3.81 IPS |
|
|
Depth Estimation (Q)
|
64% |
1240
11.3 IPS |
|
|
Style Transfer (SP)
|
100% |
930
1.20 IPS |
|
|
Style Transfer (HP)
|
100% |
899
1.16 IPS |
|
|
Style Transfer (Q)
|
98% |
2692
3.47 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
283
10.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
283
10.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1006
37.3 IPS |
|
|
Text Classification (SP)
|
100% |
368
490.7 IPS |
|
|
Text Classification (HP)
|
100% |
369
492.0 IPS |
|
|
Text Classification (Q)
|
91% |
617
830.0 IPS |
|
|
Machine Translation (SP)
|
100% |
672
11.6 IPS |
|
|
Machine Translation (HP)
|
100% |
623
10.7 IPS |
|
|
Machine Translation (Q)
|
57% |
419
10.2 IPS |
