samsung SM-F966U1
Geekbench AI Score
463
Single Precision Score
26352
Half Precision Score
59229
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | VenomF5 |
| Upload Date | July 25 2025 12:51 AM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | QNN |
| 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% |
449
83.4 IPS |
|
|
Image Classification (HP)
|
100% |
21311
3.96 KIPS |
|
|
Image Classification (Q)
|
97% |
50010
9.33 KIPS |
|
|
Image Segmentation (SP)
|
100% |
513
8.32 IPS |
|
|
Image Segmentation (HP)
|
100% |
13457
218.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
39326
639.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
408
0.48 IPS |
|
|
Pose Estimation (HP)
|
100% |
122784
143.3 IPS |
|
|
Pose Estimation (Q)
|
98% |
477209
558.5 IPS |
|
|
Object Detection (SP)
|
100% |
288
22.9 IPS |
|
|
Object Detection (HP)
|
100% |
17889
1.42 KIPS |
|
|
Object Detection (Q)
|
85% |
21143
1.70 KIPS |
|
|
Face Detection (SP)
|
100% |
595
7.07 IPS |
|
|
Face Detection (HP)
|
100% |
38127
453.0 IPS |
|
|
Face Detection (Q)
|
97% |
126700
1.51 KIPS |
|
|
Depth Estimation (SP)
|
100% |
532
4.10 IPS |
|
|
Depth Estimation (HP)
|
99% |
80795
622.5 IPS |
|
|
Depth Estimation (Q)
|
63% |
142074
1.32 KIPS |
|
|
Style Transfer (SP)
|
100% |
897
1.15 IPS |
|
|
Style Transfer (HP)
|
98% |
98283
126.7 IPS |
|
|
Style Transfer (Q)
|
98% |
490283
632.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
302
11.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
51814
1.91 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
134065
4.97 KIPS |
|
|
Text Classification (SP)
|
100% |
363
483.9 IPS |
|
|
Text Classification (HP)
|
100% |
3879
5.18 KIPS |
|
|
Text Classification (Q)
|
93% |
7977
10.7 KIPS |
|
|
Machine Translation (SP)
|
100% |
548
9.44 IPS |
|
|
Machine Translation (HP)
|
100% |
4214
72.6 IPS |
|
|
Machine Translation (Q)
|
56% |
2837
73.1 IPS |
