samsung SM-F766B
Geekbench AI Score
3921
Single Precision Score
33389
Half Precision Score
51750
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | July 10 2025 06:29 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | ENN |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | samsung SM-F766B |
| Model ID | samsung SM-F766B |
| 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% |
1628
302.7 IPS |
|
|
Image Classification (HP)
|
100% |
20435
3.80 KIPS |
|
|
Image Classification (Q)
|
100% |
42886
7.98 KIPS |
|
|
Image Segmentation (SP)
|
100% |
3230
52.4 IPS |
|
|
Image Segmentation (HP)
|
97% |
15726
255.8 IPS |
|
|
Image Segmentation (Q)
|
96% |
36489
593.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
17434
20.3 IPS |
|
|
Pose Estimation (HP)
|
100% |
147659
172.3 IPS |
|
|
Pose Estimation (Q)
|
97% |
340590
398.8 IPS |
|
|
Object Detection (SP)
|
100% |
1811
143.6 IPS |
|
|
Object Detection (HP)
|
100% |
18266
1.45 KIPS |
|
|
Object Detection (Q)
|
88% |
27270
2.19 KIPS |
|
|
Face Detection (SP)
|
100% |
5612
66.7 IPS |
|
|
Face Detection (HP)
|
100% |
22969
272.9 IPS |
|
|
Face Detection (Q)
|
96% |
93231
1.11 KIPS |
|
|
Depth Estimation (SP)
|
100% |
8787
67.7 IPS |
|
|
Depth Estimation (HP)
|
79% |
91275
724.8 IPS |
|
|
Depth Estimation (Q)
|
63% |
148148
1.38 KIPS |
|
|
Style Transfer (SP)
|
100% |
33659
43.3 IPS |
|
|
Style Transfer (HP)
|
99% |
258739
332.6 IPS |
|
|
Style Transfer (Q)
|
98% |
337447
435.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4509
166.5 IPS |
|
|
Image Super-Resolution (HP)
|
98% |
43916
1.63 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
45107
1.67 KIPS |
|
|
Text Classification (SP)
|
100% |
519
693.0 IPS |
|
|
Text Classification (HP)
|
100% |
9216
12.3 KIPS |
|
|
Text Classification (Q)
|
93% |
9449
12.7 KIPS |
|
|
Machine Translation (SP)
|
100% |
1334
23.0 IPS |
|
|
Machine Translation (HP)
|
100% |
9052
155.9 IPS |
|
|
Machine Translation (Q)
|
48% |
4772
184.5 IPS |
