samsung SM-F766U
Geekbench AI Score
3854
Single Precision Score
33364
Half Precision Score
51484
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| User | kent_tester |
| Upload Date | August 13 2025 07:07 PM |
| Views | 4 |
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% |
1656
307.9 IPS |
|
|
Image Classification (HP)
|
100% |
20808
3.87 KIPS |
|
|
Image Classification (Q)
|
100% |
42319
7.87 KIPS |
|
|
Image Segmentation (SP)
|
100% |
3246
52.6 IPS |
|
|
Image Segmentation (HP)
|
97% |
16183
263.3 IPS |
|
|
Image Segmentation (Q)
|
96% |
37504
610.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
16217
18.9 IPS |
|
|
Pose Estimation (HP)
|
100% |
150318
175.4 IPS |
|
|
Pose Estimation (Q)
|
97% |
338023
395.8 IPS |
|
|
Object Detection (SP)
|
100% |
1787
141.8 IPS |
|
|
Object Detection (HP)
|
100% |
16277
1.29 KIPS |
|
|
Object Detection (Q)
|
88% |
27152
2.18 KIPS |
|
|
Face Detection (SP)
|
100% |
5527
65.7 IPS |
|
|
Face Detection (HP)
|
100% |
23640
280.9 IPS |
|
|
Face Detection (Q)
|
96% |
93486
1.12 KIPS |
|
|
Depth Estimation (SP)
|
100% |
8640
66.6 IPS |
|
|
Depth Estimation (HP)
|
79% |
93372
741.5 IPS |
|
|
Depth Estimation (Q)
|
63% |
147745
1.38 KIPS |
|
|
Style Transfer (SP)
|
100% |
32436
41.7 IPS |
|
|
Style Transfer (HP)
|
99% |
261500
336.2 IPS |
|
|
Style Transfer (Q)
|
98% |
323887
417.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4371
161.4 IPS |
|
|
Image Super-Resolution (HP)
|
98% |
44991
1.67 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
45954
1.70 KIPS |
|
|
Text Classification (SP)
|
100% |
514
685.8 IPS |
|
|
Text Classification (HP)
|
100% |
8948
11.9 KIPS |
|
|
Text Classification (Q)
|
93% |
9355
12.6 KIPS |
|
|
Machine Translation (SP)
|
100% |
1334
23.0 IPS |
|
|
Machine Translation (HP)
|
100% |
8928
153.8 IPS |
|
|
Machine Translation (Q)
|
48% |
4671
180.6 IPS |
