samsung SM-F766N
Geekbench AI Score
342
Single Precision Score
334
Half Precision Score
678
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | August 12 2025 11:46 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| 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% |
361
67.1 IPS |
|
|
Image Classification (HP)
|
100% |
353
65.6 IPS |
|
|
Image Classification (Q)
|
99% |
692
129.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
291
4.71 IPS |
|
|
Image Segmentation (HP)
|
100% |
274
4.44 IPS |
|
|
Image Segmentation (Q)
|
98% |
522
8.48 IPS |
|
|
Pose Estimation (SP)
|
100% |
347
0.40 IPS |
|
|
Pose Estimation (HP)
|
100% |
334
0.39 IPS |
|
|
Pose Estimation (Q)
|
98% |
1408
1.65 IPS |
|
|
Object Detection (SP)
|
100% |
196
15.5 IPS |
|
|
Object Detection (HP)
|
100% |
197
15.6 IPS |
|
|
Object Detection (Q)
|
87% |
480
38.5 IPS |
|
|
Face Detection (SP)
|
100% |
497
5.90 IPS |
|
|
Face Detection (HP)
|
100% |
485
5.77 IPS |
|
|
Face Detection (Q)
|
97% |
1069
12.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
408
3.14 IPS |
|
|
Depth Estimation (HP)
|
99% |
409
3.15 IPS |
|
|
Depth Estimation (Q)
|
64% |
926
8.40 IPS |
|
|
Style Transfer (SP)
|
100% |
633
0.81 IPS |
|
|
Style Transfer (HP)
|
100% |
575
0.74 IPS |
|
|
Style Transfer (Q)
|
98% |
1390
1.79 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
207
7.64 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
212
7.81 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
703
26.0 IPS |
|
|
Text Classification (SP)
|
100% |
260
347.1 IPS |
|
|
Text Classification (HP)
|
100% |
281
374.8 IPS |
|
|
Text Classification (Q)
|
91% |
380
510.7 IPS |
|
|
Machine Translation (SP)
|
100% |
445
7.66 IPS |
|
|
Machine Translation (HP)
|
100% |
411
7.08 IPS |
|
|
Machine Translation (Q)
|
57% |
231
5.64 IPS |
