samsung SM-X910
Geekbench AI Score
2236
Single Precision Score
2275
Half Precision Score
3518
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| User | zhanzju |
| Upload Date | October 02 2024 01:38 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | samsung SM-X910 |
| Model ID | samsung SM-X910 |
| Motherboard | kalama |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3406 revision 0 |
| Base Frequency | 2.02 GHz |
| Cluster 1 | 3 Cores @ 2.02 GHz |
| Cluster 2 | 4 Cores @ 2.80 GHz |
| Cluster 3 | 1 Core @ 3.36 GHz |
| Memory Information | |
|---|---|
| Size | 10.91 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1907
354.7 IPS |
|
|
Image Classification (HP)
|
100% |
1912
355.6 IPS |
|
|
Image Classification (Q)
|
100% |
2862
532.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
2035
33.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
2129
34.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
3294
53.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
3117
3.64 IPS |
|
|
Pose Estimation (HP)
|
100% |
3159
3.69 IPS |
|
|
Pose Estimation (Q)
|
84% |
6982
8.28 IPS |
|
|
Object Detection (SP)
|
98% |
1704
135.6 IPS |
|
|
Object Detection (HP)
|
98% |
1735
138.0 IPS |
|
|
Object Detection (Q)
|
83% |
2620
211.6 IPS |
|
|
Face Detection (SP)
|
100% |
3082
36.6 IPS |
|
|
Face Detection (HP)
|
100% |
3303
39.2 IPS |
|
|
Face Detection (Q)
|
95% |
5851
69.8 IPS |
|
|
Depth Estimation (SP)
|
99% |
3121
24.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
3266
25.2 IPS |
|
|
Depth Estimation (Q)
|
64% |
5094
46.7 IPS |
|
|
Style Transfer (SP)
|
89% |
7621
9.89 IPS |
|
|
Style Transfer (HP)
|
89% |
7486
9.72 IPS |
|
|
Style Transfer (Q)
|
98% |
14270
18.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1686
62.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1698
62.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3787
140.3 IPS |
|
|
Text Classification (SP)
|
100% |
775
1.03 KIPS |
|
|
Text Classification (HP)
|
99% |
773
1.03 KIPS |
|
|
Text Classification (Q)
|
88% |
1318
1.78 KIPS |
|
|
Machine Translation (SP)
|
100% |
1588
27.4 IPS |
|
|
Machine Translation (HP)
|
100% |
1575
27.1 IPS |
|
|
Machine Translation (Q)
|
50% |
795
28.2 IPS |
