samsung SM-F966U1 Fold 7 samsung SM-F966U1
Geekbench AI Score
408
Single Precision Score
409
Half Precision Score
873
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | jeradhill |
| Upload Date | September 03 2025 03:27 AM |
| Views | 5 |
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 | 10.85 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
179
33.2 IPS |
|
|
Image Classification (HP)
|
100% |
204
37.9 IPS |
|
|
Image Classification (Q)
|
99% |
585
109.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
347
5.63 IPS |
|
|
Image Segmentation (HP)
|
100% |
348
5.64 IPS |
|
|
Image Segmentation (Q)
|
98% |
648
10.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
471
0.55 IPS |
|
|
Pose Estimation (HP)
|
100% |
437
0.51 IPS |
|
|
Pose Estimation (Q)
|
98% |
1685
1.97 IPS |
|
|
Object Detection (SP)
|
100% |
241
19.1 IPS |
|
|
Object Detection (HP)
|
100% |
242
19.2 IPS |
|
|
Object Detection (Q)
|
87% |
633
50.8 IPS |
|
|
Face Detection (SP)
|
100% |
639
7.60 IPS |
|
|
Face Detection (HP)
|
100% |
640
7.60 IPS |
|
|
Face Detection (Q)
|
97% |
1234
14.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
495
3.81 IPS |
|
|
Depth Estimation (HP)
|
99% |
495
3.82 IPS |
|
|
Depth Estimation (Q)
|
64% |
1039
9.42 IPS |
|
|
Style Transfer (SP)
|
100% |
887
1.14 IPS |
|
|
Style Transfer (HP)
|
100% |
858
1.10 IPS |
|
|
Style Transfer (Q)
|
98% |
2313
2.98 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
264
9.76 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
290
10.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1020
37.8 IPS |
|
|
Text Classification (SP)
|
100% |
369
492.0 IPS |
|
|
Text Classification (HP)
|
100% |
369
492.2 IPS |
|
|
Text Classification (Q)
|
91% |
567
762.0 IPS |
|
|
Machine Translation (SP)
|
100% |
677
11.7 IPS |
|
|
Machine Translation (HP)
|
100% |
609
10.5 IPS |
|
|
Machine Translation (Q)
|
57% |
375
9.17 IPS |
