Samsung Galaxy Z Flip7 samsung SM-F766B
Geekbench AI Score
1772
Single Precision Score
2751
Half Precision Score
2083
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | rennsport |
| Upload Date | February 08 2026 12:25 PM |
| Views | 12 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | samsung SM-F766B |
| Model ID | samsung SM-F766B |
| Motherboard | s5e9955 |
| Governor | energy_aware |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 10 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3461 revision 1 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 2 Cores @ 1.80 GHz |
| Cluster 2 | 5 Cores @ 2.36 GHz |
| Cluster 3 | 2 Cores @ 2.75 GHz |
| Cluster 4 | 1 Core @ 3.30 GHz |
| Memory Information | |
|---|---|
| Size | 10.95 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1072
199.4 IPS |
|
|
Image Classification (HP)
|
100% |
1470
273.4 IPS |
|
|
Image Classification (Q)
|
100% |
1437
267.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
2121
34.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
3417
55.4 IPS |
|
|
Image Segmentation (Q)
|
98% |
3100
50.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
8990
10.5 IPS |
|
|
Pose Estimation (HP)
|
99% |
15952
18.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
15844
18.6 IPS |
|
|
Object Detection (SP)
|
100% |
820
65.1 IPS |
|
|
Object Detection (HP)
|
99% |
1180
93.6 IPS |
|
|
Object Detection (Q)
|
84% |
1170
94.4 IPS |
|
|
Face Detection (SP)
|
100% |
4099
48.7 IPS |
|
|
Face Detection (HP)
|
100% |
5695
67.7 IPS |
|
|
Face Detection (Q)
|
97% |
4856
57.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
4989
38.4 IPS |
|
|
Depth Estimation (HP)
|
98% |
7467
57.7 IPS |
|
|
Depth Estimation (Q)
|
62% |
5841
56.3 IPS |
|
|
Style Transfer (SP)
|
100% |
18300
23.5 IPS |
|
|
Style Transfer (HP)
|
100% |
29013
37.3 IPS |
|
|
Style Transfer (Q)
|
98% |
28517
36.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2717
100.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
4424
163.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
4067
150.7 IPS |
|
|
Text Classification (SP)
|
29% |
21
356.6 IPS |
|
|
Text Classification (HP)
|
35% |
42
380.9 IPS |
|
|
Text Classification (Q)
|
29% |
26
450.2 IPS |
|
|
Machine Translation (SP)
|
100% |
854
14.7 IPS |
|
|
Machine Translation (HP)
|
100% |
1148
19.8 IPS |
|
|
Machine Translation (Q)
|
42% |
218
14.1 IPS |
