samsung SM-F766N
Geekbench AI Score
274
Single Precision Score
272
Half Precision Score
587
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | November 15 2025 03:33 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% |
167
31.0 IPS |
|
|
Image Classification (HP)
|
100% |
167
31.1 IPS |
|
|
Image Classification (Q)
|
99% |
394
73.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
223
3.62 IPS |
|
|
Image Segmentation (HP)
|
100% |
225
3.64 IPS |
|
|
Image Segmentation (Q)
|
98% |
444
7.22 IPS |
|
|
Pose Estimation (SP)
|
100% |
290
0.34 IPS |
|
|
Pose Estimation (HP)
|
100% |
285
0.33 IPS |
|
|
Pose Estimation (Q)
|
98% |
1078
1.26 IPS |
|
|
Object Detection (SP)
|
100% |
165
13.1 IPS |
|
|
Object Detection (HP)
|
100% |
165
13.1 IPS |
|
|
Object Detection (Q)
|
87% |
408
32.8 IPS |
|
|
Face Detection (SP)
|
100% |
472
5.61 IPS |
|
|
Face Detection (HP)
|
100% |
479
5.69 IPS |
|
|
Face Detection (Q)
|
97% |
931
11.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
381
2.93 IPS |
|
|
Depth Estimation (HP)
|
99% |
362
2.79 IPS |
|
|
Depth Estimation (Q)
|
64% |
768
6.97 IPS |
|
|
Style Transfer (SP)
|
100% |
620
0.80 IPS |
|
|
Style Transfer (HP)
|
100% |
575
0.74 IPS |
|
|
Style Transfer (Q)
|
98% |
1717
2.21 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
166
6.11 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
168
6.19 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
593
22.0 IPS |
|
|
Text Classification (SP)
|
100% |
192
256.9 IPS |
|
|
Text Classification (HP)
|
100% |
193
257.3 IPS |
|
|
Text Classification (Q)
|
91% |
316
424.5 IPS |
|
|
Machine Translation (SP)
|
100% |
386
6.65 IPS |
|
|
Machine Translation (HP)
|
100% |
392
6.75 IPS |
|
|
Machine Translation (Q)
|
57% |
278
6.80 IPS |
