Samsung Galaxy Z Fold6
Geekbench AI Score
2107
Single Precision Score
3144
Half Precision Score
2478
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| Upload Date | February 20 2026 03:43 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Qualcomm Snapdragon 8 Gen 3 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | Samsung Galaxy Z Fold6 |
| Model ID | samsung SM-F956U1 |
| Motherboard | pineapple |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.26 GHz |
| Cluster 1 | 2 Cores @ 2.27 GHz |
| Cluster 2 | 2 Cores @ 2.96 GHz |
| Cluster 3 | 3 Cores @ 3.15 GHz |
| Cluster 4 | 1 Core @ 3.40 GHz |
| Memory Information | |
|---|---|
| Size | 10.85 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1264
235.0 IPS |
|
|
Image Classification (HP)
|
100% |
1833
340.8 IPS |
|
|
Image Classification (Q)
|
100% |
2166
402.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
2924
47.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
3787
61.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
4744
77.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
11312
13.2 IPS |
|
|
Pose Estimation (HP)
|
99% |
20381
23.9 IPS |
|
|
Pose Estimation (Q)
|
96% |
19393
22.7 IPS |
|
|
Object Detection (SP)
|
100% |
1210
96.0 IPS |
|
|
Object Detection (HP)
|
99% |
1760
139.6 IPS |
|
|
Object Detection (Q)
|
87% |
1823
146.4 IPS |
|
|
Face Detection (SP)
|
100% |
4218
50.1 IPS |
|
|
Face Detection (HP)
|
100% |
8404
99.9 IPS |
|
|
Face Detection (Q)
|
97% |
5241
62.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
5687
43.8 IPS |
|
|
Depth Estimation (HP)
|
98% |
8398
64.9 IPS |
|
|
Depth Estimation (Q)
|
61% |
6390
62.9 IPS |
|
|
Style Transfer (SP)
|
100% |
14162
18.2 IPS |
|
|
Style Transfer (HP)
|
100% |
28557
36.7 IPS |
|
|
Style Transfer (Q)
|
98% |
28131
36.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2743
101.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
4205
155.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3844
142.4 IPS |
|
|
Text Classification (SP)
|
35% |
43
418.4 IPS |
|
|
Text Classification (HP)
|
35% |
56
507.5 IPS |
|
|
Text Classification (Q)
|
33% |
42
508.9 IPS |
|
|
Machine Translation (SP)
|
100% |
852
14.7 IPS |
|
|
Machine Translation (HP)
|
97% |
800
13.8 IPS |
|
|
Machine Translation (Q)
|
43% |
158
8.96 IPS |
