Acer Swift SFG14-72
Geekbench AI Score
1796
Single Precision Score
6187
Half Precision Score
9507
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| Upload Date | December 13 2024 10:38 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | NPU |
| Device | Intel(R) AI Boost |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | Acer Swift SFG14-72 |
| Motherboard | MTL Coral_MTH |
| Power Plan | Acer |
| CPU Information | |
|---|---|
| Name | Intel Core Ultra 7 155H |
| Topology | 1 Processor, 16 Cores, 22 Threads |
| Identifier | GenuineIntel Family 6 Model 170 Stepping 4 |
| Base Frequency | 1.40 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 10 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1001
186.1 IPS |
|
|
Image Classification (HP)
|
100% |
4450
827.6 IPS |
|
|
Image Classification (Q)
|
100% |
5978
1.11 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1264
20.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
2087
33.8 IPS |
|
|
Image Segmentation (Q)
|
99% |
2747
44.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
3015
3.52 IPS |
|
|
Pose Estimation (HP)
|
100% |
27642
32.3 IPS |
|
|
Pose Estimation (Q)
|
96% |
57339
67.2 IPS |
|
|
Object Detection (SP)
|
100% |
1044
82.8 IPS |
|
|
Object Detection (HP)
|
100% |
3570
283.2 IPS |
|
|
Object Detection (Q)
|
87% |
5794
465.0 IPS |
|
|
Face Detection (SP)
|
100% |
3427
40.7 IPS |
|
|
Face Detection (HP)
|
100% |
10460
124.3 IPS |
|
|
Face Detection (Q)
|
100% |
16986
201.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
2373
18.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
14235
109.7 IPS |
|
|
Depth Estimation (Q)
|
88% |
26739
208.1 IPS |
|
|
Style Transfer (SP)
|
100% |
10722
13.8 IPS |
|
|
Style Transfer (HP)
|
100% |
39670
51.0 IPS |
|
|
Style Transfer (Q)
|
98% |
67665
87.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1531
56.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
9379
346.3 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
15547
575.7 IPS |
|
|
Text Classification (SP)
|
100% |
608
811.7 IPS |
|
|
Text Classification (HP)
|
100% |
845
1.13 KIPS |
|
|
Text Classification (Q)
|
92% |
1221
1.64 KIPS |
|
|
Machine Translation (SP)
|
100% |
1083
18.7 IPS |
|
|
Machine Translation (HP)
|
100% |
1917
33.0 IPS |
|
|
Machine Translation (Q)
|
100% |
1896
32.7 IPS |
