Samsung Galaxy Z Flip7 samsung SM-F766B
Geekbench AI Score
3906
Single Precision Score
32550
Half Precision Score
51564
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | rennsport |
| Upload Date | February 08 2026 12:43 PM |
| Views | 25 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | ENN |
| 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% |
1659
308.5 IPS |
|
|
Image Classification (HP)
|
100% |
20952
3.90 KIPS |
|
|
Image Classification (Q)
|
100% |
42679
7.94 KIPS |
|
|
Image Segmentation (SP)
|
100% |
3292
53.4 IPS |
|
|
Image Segmentation (HP)
|
97% |
15589
253.6 IPS |
|
|
Image Segmentation (Q)
|
96% |
36610
595.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
16944
19.8 IPS |
|
|
Pose Estimation (HP)
|
100% |
146691
171.2 IPS |
|
|
Pose Estimation (Q)
|
97% |
339686
397.8 IPS |
|
|
Object Detection (SP)
|
100% |
1798
142.6 IPS |
|
|
Object Detection (HP)
|
100% |
16571
1.31 KIPS |
|
|
Object Detection (Q)
|
88% |
27191
2.18 KIPS |
|
|
Face Detection (SP)
|
100% |
5566
66.1 IPS |
|
|
Face Detection (HP)
|
100% |
21990
261.3 IPS |
|
|
Face Detection (Q)
|
96% |
92457
1.10 KIPS |
|
|
Depth Estimation (SP)
|
100% |
8678
66.9 IPS |
|
|
Depth Estimation (HP)
|
79% |
90874
721.6 IPS |
|
|
Depth Estimation (Q)
|
63% |
147756
1.38 KIPS |
|
|
Style Transfer (SP)
|
100% |
33484
43.0 IPS |
|
|
Style Transfer (HP)
|
99% |
250020
321.4 IPS |
|
|
Style Transfer (Q)
|
98% |
336280
433.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4408
162.8 IPS |
|
|
Image Super-Resolution (HP)
|
98% |
41904
1.55 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
45007
1.67 KIPS |
|
|
Text Classification (SP)
|
100% |
519
693.2 IPS |
|
|
Text Classification (HP)
|
100% |
8840
11.8 KIPS |
|
|
Text Classification (Q)
|
93% |
9315
12.5 KIPS |
|
|
Machine Translation (SP)
|
100% |
1346
23.2 IPS |
|
|
Machine Translation (HP)
|
100% |
9087
156.5 IPS |
|
|
Machine Translation (Q)
|
48% |
4781
184.9 IPS |
