Samsung Galaxy Z Fold7
Geekbench AI Score
2639
Single Precision Score
3661
Half Precision Score
4854
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | VenomF5 |
| Upload Date | March 09 2026 04:53 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Qualcomm Snapdragon 8 Elite |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | Samsung Galaxy Z Fold7 |
| 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% |
1928
358.5 IPS |
|
|
Image Classification (HP)
|
100% |
2427
451.3 IPS |
|
|
Image Classification (Q)
|
99% |
4319
805.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
2446
39.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
3131
50.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
5321
86.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
5311
6.20 IPS |
|
|
Pose Estimation (HP)
|
92% |
10157
11.9 IPS |
|
|
Pose Estimation (Q)
|
96% |
12583
14.7 IPS |
|
|
Object Detection (SP)
|
98% |
1571
125.0 IPS |
|
|
Object Detection (HP)
|
97% |
2000
159.2 IPS |
|
|
Object Detection (Q)
|
85% |
3583
288.7 IPS |
|
|
Face Detection (SP)
|
100% |
3995
47.5 IPS |
|
|
Face Detection (HP)
|
100% |
6525
77.5 IPS |
|
|
Face Detection (Q)
|
97% |
8979
107.1 IPS |
|
|
Depth Estimation (SP)
|
99% |
4344
33.6 IPS |
|
|
Depth Estimation (HP)
|
98% |
7023
54.3 IPS |
|
|
Depth Estimation (Q)
|
64% |
9183
84.7 IPS |
|
|
Style Transfer (SP)
|
89% |
10737
13.9 IPS |
|
|
Style Transfer (HP)
|
88% |
12248
15.9 IPS |
|
|
Style Transfer (Q)
|
98% |
22064
28.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2019
74.6 IPS |
|
|
Image Super-Resolution (HP)
|
92% |
3961
147.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
5935
219.9 IPS |
|
|
Text Classification (SP)
|
100% |
874
1.17 KIPS |
|
|
Text Classification (HP)
|
100% |
1095
1.46 KIPS |
|
|
Text Classification (Q)
|
93% |
972
1.30 KIPS |
|
|
Machine Translation (SP)
|
100% |
1268
21.8 IPS |
|
|
Machine Translation (HP)
|
96% |
1151
19.9 IPS |
|
|
Machine Translation (Q)
|
55% |
668
17.9 IPS |
