conquest CONQUEST-S23
Geekbench AI Score
534
Single Precision Score
521
Half Precision Score
1082
Quantized Score
Geekbench AI 1.1.0 for Android AArch64
Result Information
| Upload Date | September 16 2024 12:39 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM MT6877V/ZA |
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | conquest CONQUEST-S23 |
| Model ID | conquest CONQUEST-S23 |
| Motherboard | k6877v1_64_k419 |
| CPU Information | |
|---|---|
| Name | ARM MT6877V/ZA |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 6 Cores @ 2.00 GHz |
| Cluster 2 | 2 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 11.36 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
243
45.1 IPS |
|
|
Image Classification (HP)
|
100% |
242
45.1 IPS |
|
|
Image Classification (Q)
|
100% |
754
140.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
310
5.03 IPS |
|
|
Image Segmentation (HP)
|
100% |
291
4.71 IPS |
|
|
Image Segmentation (Q)
|
98% |
813
13.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
1099
1.28 IPS |
|
|
Pose Estimation (HP)
|
100% |
1057
1.23 IPS |
|
|
Pose Estimation (Q)
|
84% |
1760
2.09 IPS |
|
|
Object Detection (SP)
|
100% |
225
17.9 IPS |
|
|
Object Detection (HP)
|
100% |
209
16.5 IPS |
|
|
Object Detection (Q)
|
83% |
691
55.8 IPS |
|
|
Face Detection (SP)
|
100% |
757
8.99 IPS |
|
|
Face Detection (HP)
|
100% |
772
9.17 IPS |
|
|
Face Detection (Q)
|
95% |
1743
20.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
977
7.53 IPS |
|
|
Depth Estimation (HP)
|
99% |
970
7.47 IPS |
|
|
Depth Estimation (Q)
|
64% |
1685
15.4 IPS |
|
|
Style Transfer (SP)
|
89% |
2002
2.60 IPS |
|
|
Style Transfer (HP)
|
89% |
1934
2.51 IPS |
|
|
Style Transfer (Q)
|
98% |
4295
5.54 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
543
20.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
548
20.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1022
37.9 IPS |
|
|
Text Classification (SP)
|
100% |
286
381.5 IPS |
|
|
Text Classification (HP)
|
100% |
284
378.8 IPS |
|
|
Text Classification (Q)
|
88% |
638
860.8 IPS |
|
|
Machine Translation (SP)
|
100% |
442
7.62 IPS |
|
|
Machine Translation (HP)
|
100% |
421
7.24 IPS |
|
|
Machine Translation (Q)
|
50% |
359
12.7 IPS |
