Microsoft Surface Duo 2
Geekbench AI Score
317
Single Precision Score
313
Half Precision Score
724
Quantized Score
Geekbench AI 1.0.0 for Android AArch64
Result Information
| Upload Date | August 17 2024 11:28 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | QNN |
| Device | Qualcomm Snapdragon 888 |
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | Microsoft Surface Duo 2 |
| Model ID | Microsoft Surface Duo 2 |
| Motherboard | surfaceduo2 |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3396 revision 0 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.42 GHz |
| Cluster 3 | 1 Core @ 2.84 GHz |
| Memory Information | |
|---|---|
| Size | 7.10 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
234
43.4 IPS |
|
|
Image Classification (HP)
|
100% |
205
38.2 IPS |
|
|
Image Classification (Q)
|
97% |
520
97.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
239
3.87 IPS |
|
|
Image Segmentation (HP)
|
100% |
263
4.26 IPS |
|
|
Image Segmentation (Q)
|
98% |
524
8.52 IPS |
|
|
Pose Estimation (SP)
|
100% |
337
0.39 IPS |
|
|
Pose Estimation (HP)
|
100% |
339
0.40 IPS |
|
|
Pose Estimation (Q)
|
98% |
1469
1.72 IPS |
|
|
Object Detection (SP)
|
100% |
185
14.6 IPS |
|
|
Object Detection (HP)
|
100% |
185
14.7 IPS |
|
|
Object Detection (Q)
|
89% |
513
41.1 IPS |
|
|
Face Detection (SP)
|
100% |
456
5.42 IPS |
|
|
Face Detection (HP)
|
100% |
461
5.47 IPS |
|
|
Face Detection (Q)
|
97% |
1010
12.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
408
3.14 IPS |
|
|
Depth Estimation (HP)
|
100% |
409
3.15 IPS |
|
|
Depth Estimation (Q)
|
73% |
1059
8.66 IPS |
|
|
Style Transfer (SP)
|
100% |
662
0.85 IPS |
|
|
Style Transfer (HP)
|
100% |
600
0.77 IPS |
|
|
Style Transfer (Q)
|
98% |
1683
2.17 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
198
7.32 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
199
7.33 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
853
31.6 IPS |
|
|
Text Classification (SP)
|
100% |
286
381.2 IPS |
|
|
Text Classification (HP)
|
100% |
285
381.0 IPS |
|
|
Text Classification (Q)
|
91% |
441
593.0 IPS |
|
|
Machine Translation (SP)
|
100% |
428
7.37 IPS |
|
|
Machine Translation (HP)
|
100% |
425
7.32 IPS |
|
|
Machine Translation (Q)
|
57% |
286
6.98 IPS |
