Samsung Galaxy Z Fold7
Geekbench AI Score
2790
Single Precision Score
4428
Half Precision Score
3688
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | VenomF5 |
| Upload Date | March 09 2026 05:01 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| 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% |
1775
330.1 IPS |
|
|
Image Classification (HP)
|
100% |
2329
433.1 IPS |
|
|
Image Classification (Q)
|
100% |
2143
398.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
3025
49.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
5876
95.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
5040
81.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
13779
16.1 IPS |
|
|
Pose Estimation (HP)
|
99% |
24873
29.0 IPS |
|
|
Pose Estimation (Q)
|
95% |
24633
28.9 IPS |
|
|
Object Detection (SP)
|
100% |
1628
129.1 IPS |
|
|
Object Detection (HP)
|
99% |
2232
177.0 IPS |
|
|
Object Detection (Q)
|
85% |
2128
171.3 IPS |
|
|
Face Detection (SP)
|
100% |
5754
68.4 IPS |
|
|
Face Detection (HP)
|
100% |
10897
129.5 IPS |
|
|
Face Detection (Q)
|
97% |
9251
110.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
7099
54.7 IPS |
|
|
Depth Estimation (HP)
|
98% |
9664
74.7 IPS |
|
|
Depth Estimation (Q)
|
61% |
7596
74.0 IPS |
|
|
Style Transfer (SP)
|
100% |
17002
21.9 IPS |
|
|
Style Transfer (HP)
|
100% |
33673
43.3 IPS |
|
|
Style Transfer (Q)
|
98% |
35645
46.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3513
129.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5712
210.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
5401
200.2 IPS |
|
|
Text Classification (SP)
|
35% |
86
833.1 IPS |
|
|
Text Classification (HP)
|
35% |
97
881.0 IPS |
|
|
Text Classification (Q)
|
33% |
78
878.2 IPS |
|
|
Machine Translation (SP)
|
100% |
1133
19.5 IPS |
|
|
Machine Translation (HP)
|
100% |
1942
33.5 IPS |
|
|
Machine Translation (Q)
|
48% |
781
30.0 IPS |
