samsung SM-F766B
Geekbench AI Score
1865
Single Precision Score
1838
Half Precision Score
3062
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | August 31 2025 10:18 AM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
1194
222.0 IPS |
|
|
Image Classification (HP)
|
100% |
1296
240.9 IPS |
|
|
Image Classification (Q)
|
100% |
2539
472.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
1646
26.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
1698
27.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
2922
47.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
3567
4.16 IPS |
|
|
Pose Estimation (HP)
|
100% |
3556
4.15 IPS |
|
|
Pose Estimation (Q)
|
84% |
8409
9.97 IPS |
|
|
Object Detection (SP)
|
98% |
1204
95.8 IPS |
|
|
Object Detection (HP)
|
98% |
1164
92.6 IPS |
|
|
Object Detection (Q)
|
83% |
2073
167.5 IPS |
|
|
Face Detection (SP)
|
100% |
2749
32.7 IPS |
|
|
Face Detection (HP)
|
100% |
2643
31.4 IPS |
|
|
Face Detection (Q)
|
95% |
5386
64.3 IPS |
|
|
Depth Estimation (SP)
|
99% |
3157
24.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
3088
23.9 IPS |
|
|
Depth Estimation (Q)
|
64% |
4424
40.5 IPS |
|
|
Style Transfer (SP)
|
89% |
7988
10.4 IPS |
|
|
Style Transfer (HP)
|
89% |
7965
10.3 IPS |
|
|
Style Transfer (Q)
|
98% |
16281
21.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1435
53.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1413
52.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3743
138.7 IPS |
|
|
Text Classification (SP)
|
100% |
597
796.3 IPS |
|
|
Text Classification (HP)
|
99% |
600
801.0 IPS |
|
|
Text Classification (Q)
|
88% |
846
1.14 KIPS |
|
|
Machine Translation (SP)
|
100% |
1020
17.6 IPS |
|
|
Machine Translation (HP)
|
100% |
881
15.2 IPS |
|
|
Machine Translation (Q)
|
50% |
457
16.2 IPS |
