Acer Swift SFG14-75
Geekbench AI Score
3165
Single Precision Score
2145
Half Precision Score
8322
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| Upload Date | August 24 2025 12:24 PM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | CPU |
| Device | Intel(R) Core(TM) Ultra 9 288V |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 (64-bit) |
| Model | Acer Swift SFG14-75 |
| Motherboard | LNL Custin_LNV |
| Power Plan | Acer |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 9 288V |
| Topology | 1 Processor, 8 Cores |
| Identifier | GenuineIntel Family 6 Model 189 Stepping 1 |
| Base Frequency | 3.30 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1921
357.3 IPS |
|
|
Image Classification (HP)
|
100% |
1333
248.0 IPS |
|
|
Image Classification (Q)
|
100% |
5242
974.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
2111
34.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
1107
17.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
5170
83.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
3347
3.91 IPS |
|
|
Pose Estimation (HP)
|
100% |
2191
2.56 IPS |
|
|
Pose Estimation (Q)
|
96% |
12943
15.2 IPS |
|
|
Object Detection (SP)
|
100% |
1829
145.1 IPS |
|
|
Object Detection (HP)
|
100% |
1272
100.9 IPS |
|
|
Object Detection (Q)
|
88% |
5486
439.8 IPS |
|
|
Face Detection (SP)
|
100% |
5504
65.4 IPS |
|
|
Face Detection (HP)
|
100% |
4292
51.0 IPS |
|
|
Face Detection (Q)
|
100% |
13225
157.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
4676
36.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
3210
24.7 IPS |
|
|
Depth Estimation (Q)
|
89% |
14539
113.0 IPS |
|
|
Style Transfer (SP)
|
100% |
9965
12.8 IPS |
|
|
Style Transfer (HP)
|
100% |
6443
8.28 IPS |
|
|
Style Transfer (Q)
|
98% |
36827
47.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2117
78.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1422
52.5 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
7417
274.7 IPS |
|
|
Text Classification (SP)
|
100% |
2132
2.85 KIPS |
|
|
Text Classification (HP)
|
100% |
1398
1.87 KIPS |
|
|
Text Classification (Q)
|
92% |
4414
5.93 KIPS |
|
|
Machine Translation (SP)
|
100% |
3511
60.5 IPS |
|
|
Machine Translation (HP)
|
100% |
2845
49.0 IPS |
|
|
Machine Translation (Q)
|
100% |
3572
61.5 IPS |
