samsung SM-F966U1
Geekbench AI Score
433
Single Precision Score
423
Half Precision Score
885
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | VenomF5 |
| Upload Date | July 25 2025 12:43 AM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Qualcomm ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | samsung SM-F966U1 |
| Model ID | samsung SM-F966U1 |
| 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 | 14.75 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
431
80.2 IPS |
|
|
Image Classification (HP)
|
100% |
430
80.0 IPS |
|
|
Image Classification (Q)
|
99% |
796
148.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
349
5.66 IPS |
|
|
Image Segmentation (HP)
|
100% |
277
4.48 IPS |
|
|
Image Segmentation (Q)
|
98% |
527
8.57 IPS |
|
|
Pose Estimation (SP)
|
100% |
408
0.48 IPS |
|
|
Pose Estimation (HP)
|
100% |
390
0.46 IPS |
|
|
Pose Estimation (Q)
|
98% |
1587
1.86 IPS |
|
|
Object Detection (SP)
|
100% |
242
19.2 IPS |
|
|
Object Detection (HP)
|
100% |
239
18.9 IPS |
|
|
Object Detection (Q)
|
87% |
621
49.8 IPS |
|
|
Face Detection (SP)
|
100% |
574
6.82 IPS |
|
|
Face Detection (HP)
|
100% |
630
7.49 IPS |
|
|
Face Detection (Q)
|
97% |
1256
15.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
494
3.80 IPS |
|
|
Depth Estimation (HP)
|
99% |
494
3.80 IPS |
|
|
Depth Estimation (Q)
|
64% |
1148
10.4 IPS |
|
|
Style Transfer (SP)
|
100% |
892
1.15 IPS |
|
|
Style Transfer (HP)
|
100% |
893
1.15 IPS |
|
|
Style Transfer (Q)
|
98% |
2300
2.97 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
281
10.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
282
10.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1002
37.1 IPS |
|
|
Text Classification (SP)
|
100% |
336
448.6 IPS |
|
|
Text Classification (HP)
|
100% |
368
491.0 IPS |
|
|
Text Classification (Q)
|
91% |
567
762.2 IPS |
|
|
Machine Translation (SP)
|
100% |
662
11.4 IPS |
|
|
Machine Translation (HP)
|
100% |
582
10.0 IPS |
|
|
Machine Translation (Q)
|
57% |
381
9.31 IPS |
