samsung SM-F766U
Geekbench AI Score
3839
Single Precision Score
32854
Half Precision Score
50849
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | November 27 2025 06:00 PM |
| Views | 2 |
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% |
1621
301.4 IPS |
|
|
Image Classification (HP)
|
100% |
20830
3.87 KIPS |
|
|
Image Classification (Q)
|
100% |
42109
7.83 KIPS |
|
|
Image Segmentation (SP)
|
100% |
3240
52.5 IPS |
|
|
Image Segmentation (HP)
|
97% |
15615
254.0 IPS |
|
|
Image Segmentation (Q)
|
96% |
36460
593.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
16231
18.9 IPS |
|
|
Pose Estimation (HP)
|
100% |
150567
175.7 IPS |
|
|
Pose Estimation (Q)
|
97% |
340384
398.6 IPS |
|
|
Object Detection (SP)
|
100% |
1788
141.9 IPS |
|
|
Object Detection (HP)
|
100% |
16630
1.32 KIPS |
|
|
Object Detection (Q)
|
88% |
23745
1.90 KIPS |
|
|
Face Detection (SP)
|
100% |
5470
65.0 IPS |
|
|
Face Detection (HP)
|
100% |
22727
270.0 IPS |
|
|
Face Detection (Q)
|
96% |
93943
1.12 KIPS |
|
|
Depth Estimation (SP)
|
100% |
8567
66.0 IPS |
|
|
Depth Estimation (HP)
|
79% |
90365
717.6 IPS |
|
|
Depth Estimation (Q)
|
63% |
147237
1.37 KIPS |
|
|
Style Transfer (SP)
|
100% |
32309
41.5 IPS |
|
|
Style Transfer (HP)
|
99% |
246494
316.9 IPS |
|
|
Style Transfer (Q)
|
98% |
335893
433.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4410
162.8 IPS |
|
|
Image Super-Resolution (HP)
|
98% |
42887
1.59 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
45993
1.70 KIPS |
|
|
Text Classification (SP)
|
100% |
515
686.7 IPS |
|
|
Text Classification (HP)
|
100% |
9165
12.2 KIPS |
|
|
Text Classification (Q)
|
93% |
9598
12.9 KIPS |
|
|
Machine Translation (SP)
|
100% |
1329
22.9 IPS |
|
|
Machine Translation (HP)
|
100% |
9042
155.7 IPS |
|
|
Machine Translation (Q)
|
48% |
4541
175.6 IPS |
