samsung SM-F766U
Geekbench AI Score
3899
Single Precision Score
32181
Half Precision Score
51654
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | August 11 2025 03:38 PM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | ENN |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | samsung SM-F766U |
| Model ID | samsung SM-F766U |
| 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% |
1615
300.4 IPS |
|
|
Image Classification (HP)
|
100% |
18740
3.49 KIPS |
|
|
Image Classification (Q)
|
100% |
42278
7.86 KIPS |
|
|
Image Segmentation (SP)
|
100% |
3239
52.5 IPS |
|
|
Image Segmentation (HP)
|
97% |
14014
228.0 IPS |
|
|
Image Segmentation (Q)
|
96% |
35967
585.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
17008
19.8 IPS |
|
|
Pose Estimation (HP)
|
100% |
144068
168.1 IPS |
|
|
Pose Estimation (Q)
|
97% |
340396
398.6 IPS |
|
|
Object Detection (SP)
|
100% |
1794
142.3 IPS |
|
|
Object Detection (HP)
|
100% |
18376
1.46 KIPS |
|
|
Object Detection (Q)
|
88% |
27348
2.19 KIPS |
|
|
Face Detection (SP)
|
100% |
5697
67.7 IPS |
|
|
Face Detection (HP)
|
100% |
20873
248.0 IPS |
|
|
Face Detection (Q)
|
96% |
93071
1.11 KIPS |
|
|
Depth Estimation (SP)
|
100% |
8743
67.4 IPS |
|
|
Depth Estimation (HP)
|
79% |
89366
709.7 IPS |
|
|
Depth Estimation (Q)
|
63% |
149986
1.40 KIPS |
|
|
Style Transfer (SP)
|
100% |
33785
43.4 IPS |
|
|
Style Transfer (HP)
|
99% |
241405
310.3 IPS |
|
|
Style Transfer (Q)
|
98% |
338814
436.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4434
163.7 IPS |
|
|
Image Super-Resolution (HP)
|
98% |
44543
1.65 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
45322
1.68 KIPS |
|
|
Text Classification (SP)
|
100% |
506
675.7 IPS |
|
|
Text Classification (HP)
|
100% |
9251
12.3 KIPS |
|
|
Text Classification (Q)
|
93% |
9391
12.6 KIPS |
|
|
Machine Translation (SP)
|
100% |
1349
23.2 IPS |
|
|
Machine Translation (HP)
|
100% |
9236
159.1 IPS |
|
|
Machine Translation (Q)
|
48% |
4746
183.5 IPS |
