samsung SM-F966Z
Geekbench AI Score
672
Single Precision Score
656
Half Precision Score
1466
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | notakaos |
| Upload Date | August 05 2025 06:37 PM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Qualcomm ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | samsung SM-F966Z |
| Model ID | samsung SM-F966Z |
| 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% |
419
77.9 IPS |
|
|
Image Classification (HP)
|
100% |
397
73.9 IPS |
|
|
Image Classification (Q)
|
99% |
920
171.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
533
8.65 IPS |
|
|
Image Segmentation (HP)
|
100% |
495
8.02 IPS |
|
|
Image Segmentation (Q)
|
98% |
964
15.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
658
0.77 IPS |
|
|
Pose Estimation (HP)
|
100% |
625
0.73 IPS |
|
|
Pose Estimation (Q)
|
98% |
2499
2.93 IPS |
|
|
Object Detection (SP)
|
100% |
357
28.3 IPS |
|
|
Object Detection (HP)
|
100% |
359
28.5 IPS |
|
|
Object Detection (Q)
|
87% |
996
79.9 IPS |
|
|
Face Detection (SP)
|
100% |
965
11.5 IPS |
|
|
Face Detection (HP)
|
100% |
955
11.3 IPS |
|
|
Face Detection (Q)
|
97% |
2217
26.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
842
6.49 IPS |
|
|
Depth Estimation (HP)
|
99% |
812
6.26 IPS |
|
|
Depth Estimation (Q)
|
64% |
1932
17.5 IPS |
|
|
Style Transfer (SP)
|
100% |
1425
1.83 IPS |
|
|
Style Transfer (HP)
|
100% |
1434
1.84 IPS |
|
|
Style Transfer (Q)
|
98% |
4058
5.23 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
454
16.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
464
17.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1721
63.8 IPS |
|
|
Text Classification (SP)
|
100% |
664
886.3 IPS |
|
|
Text Classification (HP)
|
100% |
667
890.9 IPS |
|
|
Text Classification (Q)
|
91% |
1035
1.39 KIPS |
|
|
Machine Translation (SP)
|
100% |
1037
17.9 IPS |
|
|
Machine Translation (HP)
|
100% |
979
16.9 IPS |
|
|
Machine Translation (Q)
|
57% |
674
16.5 IPS |
