Samsung Galaxy Z Flip6
Geekbench AI Score
1017
Single Precision Score
1349
Half Precision Score
1343
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | BengtC |
| Upload Date | April 19 2025 09:06 AM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Qualcomm Snapdragon 8 Gen 3 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | Samsung Galaxy Z Flip6 |
| Model ID | samsung SM-F741B |
| 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% |
660
122.7 IPS |
|
|
Image Classification (HP)
|
100% |
493
91.6 IPS |
|
|
Image Classification (Q)
|
96% |
472
88.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
1063
17.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
1083
17.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
1011
16.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
1106
1.29 IPS |
|
|
Pose Estimation (HP)
|
100% |
2134
2.49 IPS |
|
|
Pose Estimation (Q)
|
96% |
2140
2.51 IPS |
|
|
Object Detection (SP)
|
100% |
630
49.9 IPS |
|
|
Object Detection (HP)
|
100% |
708
56.2 IPS |
|
|
Object Detection (Q)
|
87% |
715
57.4 IPS |
|
|
Face Detection (SP)
|
100% |
2065
24.5 IPS |
|
|
Face Detection (HP)
|
100% |
2358
28.0 IPS |
|
|
Face Detection (Q)
|
97% |
2371
28.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
1556
12.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
3195
24.7 IPS |
|
|
Depth Estimation (Q)
|
63% |
2652
24.6 IPS |
|
|
Style Transfer (SP)
|
100% |
5697
7.32 IPS |
|
|
Style Transfer (HP)
|
100% |
9322
12.0 IPS |
|
|
Style Transfer (Q)
|
98% |
9048
11.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
412
15.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1090
40.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1046
38.8 IPS |
|
|
Text Classification (SP)
|
100% |
454
605.7 IPS |
|
|
Text Classification (HP)
|
100% |
462
616.6 IPS |
|
|
Text Classification (Q)
|
91% |
750
1.01 KIPS |
|
|
Machine Translation (SP)
|
100% |
712
12.3 IPS |
|
|
Machine Translation (HP)
|
100% |
700
12.1 IPS |
|
|
Machine Translation (Q)
|
57% |
588
14.4 IPS |
