Acer Swift SFG16-72
Geekbench AI Score
2432
Single Precision Score
2474
Half Precision Score
5714
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| Upload Date | December 28 2024 02:09 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | CPU |
| Device | Intel(R) Core(TM) Ultra 7 155H |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 (64-bit) |
| Model | Acer Swift SFG16-72 |
| Motherboard | MTL Pipefish_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% |
1500
279.0 IPS |
|
|
Image Classification (HP)
|
100% |
1520
282.6 IPS |
|
|
Image Classification (Q)
|
100% |
3859
717.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
2000
32.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
2077
33.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
4033
65.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
3362
3.92 IPS |
|
|
Pose Estimation (HP)
|
100% |
3321
3.88 IPS |
|
|
Pose Estimation (Q)
|
96% |
11489
13.5 IPS |
|
|
Object Detection (SP)
|
100% |
1254
99.5 IPS |
|
|
Object Detection (HP)
|
100% |
1357
107.7 IPS |
|
|
Object Detection (Q)
|
88% |
3544
284.1 IPS |
|
|
Face Detection (SP)
|
100% |
4072
48.4 IPS |
|
|
Face Detection (HP)
|
100% |
4346
51.6 IPS |
|
|
Face Detection (Q)
|
100% |
8460
100.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
3605
27.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
3484
26.8 IPS |
|
|
Depth Estimation (Q)
|
89% |
9294
72.3 IPS |
|
|
Style Transfer (SP)
|
100% |
9343
12.0 IPS |
|
|
Style Transfer (HP)
|
100% |
9440
12.1 IPS |
|
|
Style Transfer (Q)
|
98% |
29999
38.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1770
65.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1816
67.1 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
5906
218.7 IPS |
|
|
Text Classification (SP)
|
100% |
1469
1.96 KIPS |
|
|
Text Classification (HP)
|
100% |
1409
1.88 KIPS |
|
|
Text Classification (Q)
|
92% |
2553
3.43 KIPS |
|
|
Machine Translation (SP)
|
100% |
1607
27.7 IPS |
|
|
Machine Translation (HP)
|
100% |
1654
28.5 IPS |
|
|
Machine Translation (Q)
|
100% |
1649
28.4 IPS |
