Acer Swift SFG14-73
Geekbench AI Score
2796
Single Precision Score
2761
Half Precision Score
6733
Quantized Score
Geekbench AI 1.5.0 for Windows AVX2
Result Information
| Upload Date | November 08 2025 02:00 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | CPU |
| Device | Intel(R) Core(TM) Ultra 9 185H |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | Acer Swift SFG14-73 |
| Motherboard | MTL Goldfish_MTH |
| Power Plan | Acer |
| CPU Information | |
|---|---|
| Name | Intel Core Ultra 9 185H |
| Topology | 1 Processor, 16 Cores, 22 Threads |
| Identifier | GenuineIntel Family 6 Model 170 Stepping 4 |
| Base Frequency | 2.30 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 10 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1829
340.0 IPS |
|
|
Image Classification (HP)
|
100% |
1803
335.3 IPS |
|
|
Image Classification (Q)
|
100% |
5694
1.06 KIPS |
|
|
Image Segmentation (SP)
|
100% |
2364
38.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
2419
39.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
5161
83.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
4144
4.84 IPS |
|
|
Pose Estimation (HP)
|
100% |
3483
4.06 IPS |
|
|
Pose Estimation (Q)
|
96% |
12536
14.7 IPS |
|
|
Object Detection (SP)
|
100% |
1365
108.3 IPS |
|
|
Object Detection (HP)
|
100% |
1435
113.8 IPS |
|
|
Object Detection (Q)
|
88% |
4201
336.7 IPS |
|
|
Face Detection (SP)
|
100% |
4542
54.0 IPS |
|
|
Face Detection (HP)
|
100% |
4582
54.4 IPS |
|
|
Face Detection (Q)
|
100% |
9354
111.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
3909
30.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
3852
29.7 IPS |
|
|
Depth Estimation (Q)
|
89% |
10140
78.9 IPS |
|
|
Style Transfer (SP)
|
100% |
11303
14.5 IPS |
|
|
Style Transfer (HP)
|
100% |
11019
14.2 IPS |
|
|
Style Transfer (Q)
|
98% |
33447
43.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1798
66.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1818
67.1 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
6221
230.4 IPS |
|
|
Text Classification (SP)
|
100% |
1727
2.30 KIPS |
|
|
Text Classification (HP)
|
100% |
1692
2.26 KIPS |
|
|
Text Classification (Q)
|
92% |
3263
4.38 KIPS |
|
|
Machine Translation (SP)
|
100% |
1922
33.1 IPS |
|
|
Machine Translation (HP)
|
100% |
1980
34.1 IPS |
|
|
Machine Translation (Q)
|
100% |
1923
33.1 IPS |
