Samsung Galaxy Z Fold6
Geekbench AI Score
663
Single Precision Score
1036
Half Precision Score
950
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | riussi |
| Upload Date | January 28 2025 05:08 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Qualcomm Snapdragon 8 Gen 3 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy Z Fold6 |
| Model ID | samsung SM-F956B |
| 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 | 10.86 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
824
153.2 IPS |
|
|
Image Classification (HP)
|
100% |
927
172.3 IPS |
|
|
Image Classification (Q)
|
96% |
862
160.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
1360
22.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
2261
36.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
1301
21.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
586
0.68 IPS |
|
|
Pose Estimation (HP)
|
100% |
1068
1.25 IPS |
|
|
Pose Estimation (Q)
|
96% |
1065
1.25 IPS |
|
|
Object Detection (SP)
|
100% |
324
25.7 IPS |
|
|
Object Detection (HP)
|
100% |
484
38.4 IPS |
|
|
Object Detection (Q)
|
87% |
476
38.2 IPS |
|
|
Face Detection (SP)
|
100% |
1203
14.3 IPS |
|
|
Face Detection (HP)
|
100% |
2296
27.3 IPS |
|
|
Face Detection (Q)
|
97% |
1927
23.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
782
6.02 IPS |
|
|
Depth Estimation (HP)
|
99% |
1585
12.2 IPS |
|
|
Depth Estimation (Q)
|
63% |
1310
12.1 IPS |
|
|
Style Transfer (SP)
|
100% |
2770
3.56 IPS |
|
|
Style Transfer (HP)
|
100% |
4473
5.75 IPS |
|
|
Style Transfer (Q)
|
98% |
4398
5.67 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
245
9.06 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
700
25.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
672
24.9 IPS |
|
|
Text Classification (SP)
|
100% |
273
364.3 IPS |
|
|
Text Classification (HP)
|
100% |
274
365.1 IPS |
|
|
Text Classification (Q)
|
91% |
429
576.6 IPS |
|
|
Machine Translation (SP)
|
100% |
443
7.63 IPS |
|
|
Machine Translation (HP)
|
100% |
423
7.29 IPS |
|
|
Machine Translation (Q)
|
57% |
330
8.05 IPS |
