Samsung Galaxy Note20 Ultra
Geekbench AI Score
819
Single Precision Score
805
Half Precision Score
1469
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| Upload Date | November 17 2024 04:56 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Samsung Exynos 990 |
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Samsung Galaxy Note20 Ultra |
| Model ID | samsung SM-N986B |
| Motherboard | exynos990 |
| Governor | energy_step |
| CPU Information | |
|---|---|
| Name | ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 83 architecture 8 variant 1 part 4 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores @ 2.00 GHz |
| Cluster 2 | 2 Cores @ 2.50 GHz |
| Cluster 3 | 2 Cores @ 2.73 GHz |
| Memory Information | |
|---|---|
| Size | 10.64 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
421
78.3 IPS |
|
|
Image Classification (HP)
|
100% |
400
74.5 IPS |
|
|
Image Classification (Q)
|
100% |
1091
202.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
511
8.28 IPS |
|
|
Image Segmentation (HP)
|
100% |
508
8.24 IPS |
|
|
Image Segmentation (Q)
|
98% |
1212
19.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
1929
2.25 IPS |
|
|
Pose Estimation (HP)
|
100% |
1832
2.14 IPS |
|
|
Pose Estimation (Q)
|
84% |
3020
3.58 IPS |
|
|
Object Detection (SP)
|
100% |
411
32.6 IPS |
|
|
Object Detection (HP)
|
100% |
399
31.7 IPS |
|
|
Object Detection (Q)
|
83% |
1057
85.4 IPS |
|
|
Face Detection (SP)
|
100% |
1209
14.4 IPS |
|
|
Face Detection (HP)
|
100% |
1235
14.7 IPS |
|
|
Face Detection (Q)
|
95% |
2483
29.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
1230
9.48 IPS |
|
|
Depth Estimation (HP)
|
99% |
1209
9.32 IPS |
|
|
Depth Estimation (Q)
|
64% |
2639
24.2 IPS |
|
|
Style Transfer (SP)
|
89% |
3240
4.21 IPS |
|
|
Style Transfer (HP)
|
89% |
3254
4.22 IPS |
|
|
Style Transfer (Q)
|
98% |
6489
8.37 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
767
28.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
753
27.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1578
58.5 IPS |
|
|
Text Classification (SP)
|
100% |
362
483.8 IPS |
|
|
Text Classification (HP)
|
100% |
357
476.1 IPS |
|
|
Text Classification (Q)
|
88% |
504
679.3 IPS |
|
|
Machine Translation (SP)
|
100% |
598
10.3 IPS |
|
|
Machine Translation (HP)
|
100% |
590
10.2 IPS |
|
|
Machine Translation (Q)
|
50% |
328
11.6 IPS |
