Acer Swift SFG16-73
Geekbench AI Score
4713
Single Precision Score
1926
Half Precision Score
8870
Quantized Score
Geekbench AI 1.4.0 for Windows AVX2
Result Information
| Upload Date | August 29 2025 10:42 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel(R) Core(TM) Ultra 9 285H |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | Acer Swift SFG16-73 |
| Motherboard | ARL Flatfish_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% |
3723
692.4 IPS |
|
|
Image Classification (HP)
|
100% |
745
138.6 IPS |
|
|
Image Classification (Q)
|
99% |
7975
1.49 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1764
28.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
1186
19.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
10816
175.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
7959
9.29 IPS |
|
|
Pose Estimation (HP)
|
100% |
5601
6.53 IPS |
|
|
Pose Estimation (Q)
|
94% |
27697
32.5 IPS |
|
|
Object Detection (SP)
|
100% |
3373
267.6 IPS |
|
|
Object Detection (HP)
|
100% |
953
75.6 IPS |
|
|
Object Detection (Q)
|
86% |
7468
600.2 IPS |
|
|
Face Detection (SP)
|
100% |
10403
123.6 IPS |
|
|
Face Detection (HP)
|
100% |
2019
24.0 IPS |
|
|
Face Detection (Q)
|
97% |
10631
126.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
9918
76.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
2417
18.6 IPS |
|
|
Depth Estimation (Q)
|
78% |
18025
143.8 IPS |
|
|
Style Transfer (SP)
|
100% |
18524
23.8 IPS |
|
|
Style Transfer (HP)
|
100% |
12478
16.0 IPS |
|
|
Style Transfer (Q)
|
98% |
26158
33.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3449
127.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2512
92.7 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
5892
218.2 IPS |
|
|
Text Classification (SP)
|
100% |
1829
2.44 KIPS |
|
|
Text Classification (HP)
|
100% |
914
1.22 KIPS |
|
|
Text Classification (Q)
|
97% |
1538
2.06 KIPS |
|
|
Machine Translation (SP)
|
100% |
2546
43.9 IPS |
|
|
Machine Translation (HP)
|
100% |
1070
18.4 IPS |
|
|
Machine Translation (Q)
|
65% |
3724
74.8 IPS |
