Samsung Galaxy Z Flip7 samsung SM-F766B
Geekbench AI Score
2344
Single Precision Score
2347
Half Precision Score
3823
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | rennsport |
| Upload Date | February 08 2026 12:21 PM |
| Views | 12 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
2231
414.8 IPS |
|
|
Image Classification (HP)
|
100% |
2168
403.2 IPS |
|
|
Image Classification (Q)
|
100% |
3792
705.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
2770
44.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
2744
44.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
4456
72.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
4031
4.70 IPS |
|
|
Pose Estimation (HP)
|
100% |
4005
4.67 IPS |
|
|
Pose Estimation (Q)
|
84% |
8831
10.5 IPS |
|
|
Object Detection (SP)
|
98% |
1449
115.3 IPS |
|
|
Object Detection (HP)
|
98% |
1598
127.1 IPS |
|
|
Object Detection (Q)
|
83% |
2365
191.0 IPS |
|
|
Face Detection (SP)
|
100% |
3249
38.6 IPS |
|
|
Face Detection (HP)
|
100% |
4190
49.8 IPS |
|
|
Face Detection (Q)
|
95% |
5894
70.4 IPS |
|
|
Depth Estimation (SP)
|
99% |
3434
26.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
3223
24.9 IPS |
|
|
Depth Estimation (Q)
|
64% |
6848
62.7 IPS |
|
|
Style Transfer (SP)
|
89% |
9019
11.7 IPS |
|
|
Style Transfer (HP)
|
89% |
9016
11.7 IPS |
|
|
Style Transfer (Q)
|
98% |
17652
22.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1512
55.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1522
56.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
4063
150.5 IPS |
|
|
Text Classification (SP)
|
100% |
668
891.5 IPS |
|
|
Text Classification (HP)
|
99% |
650
868.2 IPS |
|
|
Text Classification (Q)
|
88% |
1026
1.38 KIPS |
|
|
Machine Translation (SP)
|
100% |
1366
23.5 IPS |
|
|
Machine Translation (HP)
|
100% |
1108
19.1 IPS |
|
|
Machine Translation (Q)
|
50% |
637
22.6 IPS |
