Samsung SM-P580
Geekbench AI Score
10
Single Precision Score
10
Half Precision Score
6
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | October 26 2025 03:47 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung SM-P580 |
| Model ID | Samsung SM-P580 |
| Motherboard | exynos7870 |
| Governor | interactive |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3331 revision 4 |
| Base Frequency | 1.69 GHz |
| Cluster 1 | 8 Cores @ 1.69 GHz |
| Memory Information | |
|---|---|
| Size | 2.88 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
0% |
0
660.7 IPS |
|
|
Image Classification (HP)
|
0% |
0
655.0 IPS |
|
|
Image Classification (Q)
|
0% |
0
896.5 IPS |
|
|
Image Segmentation (SP)
|
73% |
3101
53.6 IPS |
|
|
Image Segmentation (HP)
|
73% |
3294
56.9 IPS |
|
|
Image Segmentation (Q)
|
73% |
9165
158.4 IPS |
|
|
Pose Estimation (SP)
|
0% |
0
209.8 IPS |
|
|
Pose Estimation (HP)
|
0% |
0
208.6 IPS |
|
|
Pose Estimation (Q)
|
0% |
0
512.0 IPS |
|
|
Object Detection (SP)
|
0% |
0
268.4 IPS |
|
|
Object Detection (HP)
|
0% |
0
273.8 IPS |
|
|
Object Detection (Q)
|
0% |
0
230.5 IPS |
|
|
Face Detection (SP)
|
0% |
0
83.0 IPS |
|
|
Face Detection (HP)
|
0% |
0
84.0 IPS |
|
|
Face Detection (Q)
|
0% |
0
143.6 IPS |
|
|
Depth Estimation (SP)
|
0% |
0
226.3 IPS |
|
|
Depth Estimation (HP)
|
0% |
0
224.8 IPS |
|
|
Depth Estimation (Q)
|
0% |
0
209.7 IPS |
|
|
Style Transfer (SP)
|
32% |
31242
391.9 IPS |
|
|
Style Transfer (HP)
|
32% |
31225
391.6 IPS |
|
|
Style Transfer (Q)
|
0% |
0
1.03 KIPS |
|
|
Image Super-Resolution (SP)
|
1% |
0
462.4 IPS |
|
|
Image Super-Resolution (HP)
|
1% |
0
454.4 IPS |
|
|
Image Super-Resolution (Q)
|
2% |
64
750.2 IPS |
|
|
Text Classification (SP)
|
29% |
146
2.51 KIPS |
|
|
Text Classification (HP)
|
29% |
149
2.57 KIPS |
|
|
Text Classification (Q)
|
29% |
109
1.88 KIPS |
|
|
Machine Translation (SP)
|
0% |
0
1.84 IPS |
|
|
Machine Translation (HP)
|
0% |
0
1.78 IPS |
|
|
Machine Translation (Q)
|
0% |
0
1.55 IPS |
