samsung SM-F766N
Geekbench AI Score
2101
Single Precision Score
2047
Half Precision Score
3515
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | August 12 2025 11:13 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% |
1653
307.4 IPS |
|
|
Image Classification (HP)
|
100% |
1739
323.4 IPS |
|
|
Image Classification (Q)
|
100% |
3637
676.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
2531
41.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
2568
41.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
4197
68.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
4660
5.44 IPS |
|
|
Pose Estimation (HP)
|
100% |
3531
4.12 IPS |
|
|
Pose Estimation (Q)
|
84% |
9026
10.7 IPS |
|
|
Object Detection (SP)
|
98% |
1280
101.9 IPS |
|
|
Object Detection (HP)
|
98% |
1294
102.9 IPS |
|
|
Object Detection (Q)
|
83% |
2218
179.2 IPS |
|
|
Face Detection (SP)
|
100% |
3013
35.8 IPS |
|
|
Face Detection (HP)
|
100% |
2505
29.8 IPS |
|
|
Face Detection (Q)
|
95% |
5413
64.6 IPS |
|
|
Depth Estimation (SP)
|
99% |
3154
24.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
3348
25.9 IPS |
|
|
Depth Estimation (Q)
|
64% |
5819
53.3 IPS |
|
|
Style Transfer (SP)
|
89% |
8616
11.2 IPS |
|
|
Style Transfer (HP)
|
89% |
8592
11.2 IPS |
|
|
Style Transfer (Q)
|
98% |
17077
22.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1471
54.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1463
54.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3943
146.1 IPS |
|
|
Text Classification (SP)
|
100% |
596
795.3 IPS |
|
|
Text Classification (HP)
|
99% |
633
844.9 IPS |
|
|
Text Classification (Q)
|
88% |
905
1.22 KIPS |
|
|
Machine Translation (SP)
|
100% |
940
16.2 IPS |
|
|
Machine Translation (HP)
|
100% |
952
16.4 IPS |
|
|
Machine Translation (Q)
|
50% |
492
17.5 IPS |
