samsung SM-F766N
Geekbench AI Score
502
Single Precision Score
493
Half Precision Score
1010
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | October 31 2025 07:29 AM |
| Views | 1 |
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% |
387
72.0 IPS |
|
|
Image Classification (HP)
|
100% |
380
70.6 IPS |
|
|
Image Classification (Q)
|
99% |
924
172.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
481
7.80 IPS |
|
|
Image Segmentation (HP)
|
100% |
484
7.84 IPS |
|
|
Image Segmentation (Q)
|
98% |
955
15.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
592
0.69 IPS |
|
|
Pose Estimation (HP)
|
100% |
584
0.68 IPS |
|
|
Pose Estimation (Q)
|
98% |
2050
2.40 IPS |
|
|
Object Detection (SP)
|
100% |
297
23.5 IPS |
|
|
Object Detection (HP)
|
100% |
295
23.4 IPS |
|
|
Object Detection (Q)
|
87% |
739
59.3 IPS |
|
|
Face Detection (SP)
|
100% |
744
8.84 IPS |
|
|
Face Detection (HP)
|
100% |
743
8.83 IPS |
|
|
Face Detection (Q)
|
97% |
1642
19.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
583
4.49 IPS |
|
|
Depth Estimation (HP)
|
99% |
551
4.24 IPS |
|
|
Depth Estimation (Q)
|
64% |
1068
9.69 IPS |
|
|
Style Transfer (SP)
|
100% |
836
1.07 IPS |
|
|
Style Transfer (HP)
|
100% |
851
1.09 IPS |
|
|
Style Transfer (Q)
|
98% |
2045
2.64 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
335
12.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
299
11.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1095
40.6 IPS |
|
|
Text Classification (SP)
|
100% |
381
509.0 IPS |
|
|
Text Classification (HP)
|
100% |
403
538.0 IPS |
|
|
Text Classification (Q)
|
91% |
541
727.1 IPS |
|
|
Machine Translation (SP)
|
100% |
675
11.6 IPS |
|
|
Machine Translation (HP)
|
100% |
650
11.2 IPS |
|
|
Machine Translation (Q)
|
57% |
389
9.51 IPS |
