samsung SM-F766N
Geekbench AI Score
1958
Single Precision Score
1904
Half Precision Score
3262
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | August 12 2025 11:18 AM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | samsung SM-F766N |
| Model ID | samsung SM-F766N |
| 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% |
1756
326.5 IPS |
|
|
Image Classification (HP)
|
100% |
1732
322.1 IPS |
|
|
Image Classification (Q)
|
100% |
3607
670.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
2552
41.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
2572
41.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
4315
70.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
3538
4.13 IPS |
|
|
Pose Estimation (HP)
|
100% |
3514
4.10 IPS |
|
|
Pose Estimation (Q)
|
84% |
7854
9.31 IPS |
|
|
Object Detection (SP)
|
98% |
1217
96.8 IPS |
|
|
Object Detection (HP)
|
98% |
1215
96.7 IPS |
|
|
Object Detection (Q)
|
83% |
2141
172.9 IPS |
|
|
Face Detection (SP)
|
100% |
2739
32.6 IPS |
|
|
Face Detection (HP)
|
100% |
2342
27.8 IPS |
|
|
Face Detection (Q)
|
95% |
5223
62.3 IPS |
|
|
Depth Estimation (SP)
|
99% |
2390
18.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
2957
22.8 IPS |
|
|
Depth Estimation (Q)
|
64% |
5475
50.1 IPS |
|
|
Style Transfer (SP)
|
89% |
8040
10.4 IPS |
|
|
Style Transfer (HP)
|
89% |
8000
10.4 IPS |
|
|
Style Transfer (Q)
|
98% |
15750
20.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1451
53.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1283
47.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3209
118.9 IPS |
|
|
Text Classification (SP)
|
100% |
545
728.1 IPS |
|
|
Text Classification (HP)
|
99% |
540
721.4 IPS |
|
|
Text Classification (Q)
|
88% |
859
1.16 KIPS |
|
|
Machine Translation (SP)
|
100% |
1036
17.8 IPS |
|
|
Machine Translation (HP)
|
100% |
862
14.9 IPS |
|
|
Machine Translation (Q)
|
50% |
420
14.9 IPS |
