Acer Swift SFG14-74
Geekbench AI Score
2919
Single Precision Score
1269
Half Precision Score
5398
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| User | cfy0713 |
| Upload Date | April 22 2025 01:16 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel(R) Core(TM) Ultra 9 285H |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 (64-bit) |
| Model | Acer Swift SFG14-74 |
| Motherboard | ARL Crayfish_ARH |
| Power Plan | Acer |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 9 285H |
| Topology | 1 Processor, 16 Cores |
| Identifier | GenuineIntel Family 6 Model 197 Stepping 2 |
| Base Frequency | 2.90 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 10 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1849
343.9 IPS |
|
|
Image Classification (HP)
|
100% |
477
88.7 IPS |
|
|
Image Classification (Q)
|
99% |
6212
1.16 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1527
24.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
863
14.0 IPS |
|
|
Image Segmentation (Q)
|
98% |
2517
40.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
6083
7.10 IPS |
|
|
Pose Estimation (HP)
|
100% |
4229
4.93 IPS |
|
|
Pose Estimation (Q)
|
94% |
13537
15.9 IPS |
|
|
Object Detection (SP)
|
100% |
1917
152.0 IPS |
|
|
Object Detection (HP)
|
100% |
600
47.6 IPS |
|
|
Object Detection (Q)
|
86% |
6984
561.3 IPS |
|
|
Face Detection (SP)
|
100% |
5600
66.5 IPS |
|
|
Face Detection (HP)
|
100% |
1323
15.7 IPS |
|
|
Face Detection (Q)
|
97% |
7086
84.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
5295
40.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
1948
15.0 IPS |
|
|
Depth Estimation (Q)
|
78% |
8971
71.6 IPS |
|
|
Style Transfer (SP)
|
100% |
9586
12.3 IPS |
|
|
Style Transfer (HP)
|
100% |
6875
8.84 IPS |
|
|
Style Transfer (Q)
|
98% |
16568
21.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1794
66.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1268
46.8 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
2684
99.4 IPS |
|
|
Text Classification (SP)
|
100% |
1569
2.09 KIPS |
|
|
Text Classification (HP)
|
100% |
642
856.6 IPS |
|
|
Text Classification (Q)
|
97% |
1590
2.13 KIPS |
|
|
Machine Translation (SP)
|
100% |
1708
29.4 IPS |
|
|
Machine Translation (HP)
|
100% |
721
12.4 IPS |
|
|
Machine Translation (Q)
|
65% |
3162
63.5 IPS |
