samsung SM-F966U1 Fold 7 samsung SM-F966U1
Geekbench AI Score
2465
Single Precision Score
3723
Half Precision Score
3194
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | jeradhill |
| Upload Date | September 03 2025 03:15 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| 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% |
1991
370.2 IPS |
|
|
Image Classification (HP)
|
100% |
2815
523.5 IPS |
|
|
Image Classification (Q)
|
100% |
2800
520.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
3285
53.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
5812
94.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
5412
88.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
13803
16.1 IPS |
|
|
Pose Estimation (HP)
|
99% |
18342
21.4 IPS |
|
|
Pose Estimation (Q)
|
95% |
17873
20.9 IPS |
|
|
Object Detection (SP)
|
100% |
1119
88.7 IPS |
|
|
Object Detection (HP)
|
99% |
1613
127.9 IPS |
|
|
Object Detection (Q)
|
85% |
1475
118.7 IPS |
|
|
Face Detection (SP)
|
100% |
4394
52.2 IPS |
|
|
Face Detection (HP)
|
100% |
7650
90.9 IPS |
|
|
Face Detection (Q)
|
97% |
7315
87.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
6004
46.3 IPS |
|
|
Depth Estimation (HP)
|
98% |
8018
62.0 IPS |
|
|
Depth Estimation (Q)
|
61% |
6586
64.2 IPS |
|
|
Style Transfer (SP)
|
100% |
13841
17.8 IPS |
|
|
Style Transfer (HP)
|
100% |
29806
38.3 IPS |
|
|
Style Transfer (Q)
|
98% |
31954
41.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3223
119.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
4908
181.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
4755
176.2 IPS |
|
|
Text Classification (SP)
|
35% |
73
709.5 IPS |
|
|
Text Classification (HP)
|
35% |
73
667.5 IPS |
|
|
Text Classification (Q)
|
33% |
65
733.1 IPS |
|
|
Machine Translation (SP)
|
100% |
957
16.5 IPS |
|
|
Machine Translation (HP)
|
100% |
1617
27.9 IPS |
|
|
Machine Translation (Q)
|
48% |
582
22.3 IPS |
