Microsoft Surface Duo 2
Geekbench AI Score
342
Single Precision Score
338
Half Precision Score
656
Quantized Score
Geekbench AI 1.0.0 for Android AArch64
Result Information
| Upload Date | August 18 2024 09:36 AM |
| Views | 15 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
174
32.4 IPS |
|
|
Image Classification (HP)
|
100% |
174
32.4 IPS |
|
|
Image Classification (Q)
|
100% |
470
87.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
184
2.98 IPS |
|
|
Image Segmentation (HP)
|
100% |
173
2.81 IPS |
|
|
Image Segmentation (Q)
|
98% |
502
8.17 IPS |
|
|
Pose Estimation (SP)
|
100% |
1351
1.58 IPS |
|
|
Pose Estimation (HP)
|
100% |
1357
1.58 IPS |
|
|
Pose Estimation (Q)
|
84% |
1903
2.26 IPS |
|
|
Object Detection (SP)
|
100% |
172
13.7 IPS |
|
|
Object Detection (HP)
|
100% |
170
13.5 IPS |
|
|
Object Detection (Q)
|
87% |
479
38.4 IPS |
|
|
Face Detection (SP)
|
100% |
381
4.52 IPS |
|
|
Face Detection (HP)
|
100% |
388
4.62 IPS |
|
|
Face Detection (Q)
|
95% |
914
10.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
516
3.98 IPS |
|
|
Depth Estimation (HP)
|
100% |
527
4.06 IPS |
|
|
Depth Estimation (Q)
|
75% |
1144
9.27 IPS |
|
|
Style Transfer (SP)
|
89% |
1132
1.47 IPS |
|
|
Style Transfer (HP)
|
89% |
1121
1.45 IPS |
|
|
Style Transfer (Q)
|
98% |
2332
3.01 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
315
11.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
296
10.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
641
23.8 IPS |
|
|
Text Classification (SP)
|
100% |
173
231.3 IPS |
|
|
Text Classification (HP)
|
100% |
172
229.1 IPS |
|
|
Text Classification (Q)
|
88% |
277
373.3 IPS |
|
|
Machine Translation (SP)
|
100% |
249
4.28 IPS |
|
|
Machine Translation (HP)
|
100% |
244
4.20 IPS |
|
|
Machine Translation (Q)
|
50% |
160
5.69 IPS |
