samsung SM-F766N
Geekbench AI Score
2094
Single Precision Score
2100
Half Precision Score
3418
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | November 30 2025 02:32 PM |
| Views | 1 |
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% |
1392
259.0 IPS |
|
|
Image Classification (HP)
|
100% |
1410
262.2 IPS |
|
|
Image Classification (Q)
|
100% |
2580
479.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
1777
28.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
1898
30.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
3016
49.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
3775
4.40 IPS |
|
|
Pose Estimation (HP)
|
100% |
3717
4.34 IPS |
|
|
Pose Estimation (Q)
|
84% |
8780
10.4 IPS |
|
|
Object Detection (SP)
|
98% |
1482
118.0 IPS |
|
|
Object Detection (HP)
|
98% |
1473
117.2 IPS |
|
|
Object Detection (Q)
|
83% |
2350
189.9 IPS |
|
|
Face Detection (SP)
|
100% |
3153
37.5 IPS |
|
|
Face Detection (HP)
|
100% |
3085
36.7 IPS |
|
|
Face Detection (Q)
|
95% |
6054
72.3 IPS |
|
|
Depth Estimation (SP)
|
99% |
3619
28.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
3635
28.1 IPS |
|
|
Depth Estimation (Q)
|
64% |
6146
56.3 IPS |
|
|
Style Transfer (SP)
|
89% |
8715
11.3 IPS |
|
|
Style Transfer (HP)
|
89% |
9103
11.8 IPS |
|
|
Style Transfer (Q)
|
98% |
16450
21.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1543
57.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1581
58.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
4028
149.3 IPS |
|
|
Text Classification (SP)
|
100% |
627
837.5 IPS |
|
|
Text Classification (HP)
|
99% |
629
839.5 IPS |
|
|
Text Classification (Q)
|
88% |
961
1.30 KIPS |
|
|
Machine Translation (SP)
|
100% |
1220
21.0 IPS |
|
|
Machine Translation (HP)
|
100% |
1125
19.4 IPS |
|
|
Machine Translation (Q)
|
50% |
573
20.3 IPS |
