samsung SM-F766B
Geekbench AI Score
3877
Single Precision Score
32916
Half Precision Score
50659
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | July 09 2025 07:49 PM |
| Views | 9 |
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% |
1602
297.9 IPS |
|
|
Image Classification (HP)
|
100% |
21133
3.93 KIPS |
|
|
Image Classification (Q)
|
100% |
43003
8.00 KIPS |
|
|
Image Segmentation (SP)
|
100% |
3326
53.9 IPS |
|
|
Image Segmentation (HP)
|
97% |
15318
249.2 IPS |
|
|
Image Segmentation (Q)
|
96% |
36642
596.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
16994
19.8 IPS |
|
|
Pose Estimation (HP)
|
100% |
150317
175.4 IPS |
|
|
Pose Estimation (Q)
|
97% |
340883
399.2 IPS |
|
|
Object Detection (SP)
|
100% |
1781
141.3 IPS |
|
|
Object Detection (HP)
|
100% |
16596
1.32 KIPS |
|
|
Object Detection (Q)
|
88% |
23993
1.92 KIPS |
|
|
Face Detection (SP)
|
100% |
5592
66.4 IPS |
|
|
Face Detection (HP)
|
100% |
22991
273.2 IPS |
|
|
Face Detection (Q)
|
96% |
93551
1.12 KIPS |
|
|
Depth Estimation (SP)
|
100% |
8642
66.6 IPS |
|
|
Depth Estimation (HP)
|
79% |
89465
710.4 IPS |
|
|
Depth Estimation (Q)
|
63% |
137010
1.28 KIPS |
|
|
Style Transfer (SP)
|
100% |
32790
42.2 IPS |
|
|
Style Transfer (HP)
|
99% |
249882
321.2 IPS |
|
|
Style Transfer (Q)
|
98% |
336272
433.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4507
166.4 IPS |
|
|
Image Super-Resolution (HP)
|
98% |
43038
1.59 KIPS |
|
|
Image Super-Resolution (Q)
|
97% |
44986
1.67 KIPS |
|
|
Text Classification (SP)
|
100% |
503
671.1 IPS |
|
|
Text Classification (HP)
|
100% |
9147
12.2 KIPS |
|
|
Text Classification (Q)
|
93% |
9487
12.7 KIPS |
|
|
Machine Translation (SP)
|
100% |
1325
22.8 IPS |
|
|
Machine Translation (HP)
|
100% |
9140
157.4 IPS |
|
|
Machine Translation (Q)
|
48% |
4696
181.6 IPS |
