samsung SM-F766B
Geekbench AI Score
382
Single Precision Score
356
Half Precision Score
727
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | July 25 2025 03:36 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| 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% |
365
67.8 IPS |
|
|
Image Classification (HP)
|
100% |
367
68.2 IPS |
|
|
Image Classification (Q)
|
99% |
712
132.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
394
6.38 IPS |
|
|
Image Segmentation (HP)
|
100% |
347
5.62 IPS |
|
|
Image Segmentation (Q)
|
98% |
585
9.51 IPS |
|
|
Pose Estimation (SP)
|
100% |
381
0.44 IPS |
|
|
Pose Estimation (HP)
|
100% |
327
0.38 IPS |
|
|
Pose Estimation (Q)
|
98% |
1394
1.63 IPS |
|
|
Object Detection (SP)
|
100% |
200
15.8 IPS |
|
|
Object Detection (HP)
|
100% |
205
16.3 IPS |
|
|
Object Detection (Q)
|
87% |
505
40.5 IPS |
|
|
Face Detection (SP)
|
100% |
545
6.48 IPS |
|
|
Face Detection (HP)
|
100% |
524
6.23 IPS |
|
|
Face Detection (Q)
|
97% |
1097
13.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
458
3.53 IPS |
|
|
Depth Estimation (HP)
|
99% |
437
3.37 IPS |
|
|
Depth Estimation (Q)
|
64% |
1009
9.16 IPS |
|
|
Style Transfer (SP)
|
100% |
655
0.84 IPS |
|
|
Style Transfer (HP)
|
100% |
603
0.78 IPS |
|
|
Style Transfer (Q)
|
98% |
1450
1.87 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
235
8.66 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
222
8.21 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
754
28.0 IPS |
|
|
Text Classification (SP)
|
100% |
298
397.7 IPS |
|
|
Text Classification (HP)
|
100% |
280
373.3 IPS |
|
|
Text Classification (Q)
|
91% |
460
617.8 IPS |
|
|
Machine Translation (SP)
|
100% |
535
9.22 IPS |
|
|
Machine Translation (HP)
|
100% |
447
7.70 IPS |
|
|
Machine Translation (Q)
|
57% |
253
6.18 IPS |
