Acer Swift SFE14-51T Windows11 ONNX CPU Acer Swift SFE14-51T
Geekbench AI Score
2942
Single Precision Score
1374
Half Precision Score
6461
Quantized Score
Geekbench AI 1.7.0 for Windows AVX2
Result Information
| User | diegotomc |
| Upload Date | March 27 2026 03:12 AM |
| Views | 11 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel(R) Core(TM) Ultra 9 288V |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | Acer Swift SFE14-51T |
| Motherboard | LNL Sunfish_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% |
2500
464.9 IPS |
|
|
Image Classification (HP)
|
100% |
516
96.0 IPS |
|
|
Image Classification (Q)
|
99% |
5457
1.02 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1491
24.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
917
14.9 IPS |
|
|
Image Segmentation (Q)
|
98% |
7309
118.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
5043
5.88 IPS |
|
|
Pose Estimation (HP)
|
100% |
3468
4.05 IPS |
|
|
Pose Estimation (Q)
|
94% |
17818
20.9 IPS |
|
|
Object Detection (SP)
|
100% |
2291
181.7 IPS |
|
|
Object Detection (HP)
|
100% |
673
53.4 IPS |
|
|
Object Detection (Q)
|
86% |
5370
431.6 IPS |
|
|
Face Detection (SP)
|
100% |
6638
78.9 IPS |
|
|
Face Detection (HP)
|
100% |
1619
19.2 IPS |
|
|
Face Detection (Q)
|
97% |
8405
100.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
6437
49.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
2019
15.6 IPS |
|
|
Depth Estimation (Q)
|
78% |
13224
105.5 IPS |
|
|
Style Transfer (SP)
|
100% |
4440
5.71 IPS |
|
|
Style Transfer (HP)
|
100% |
8783
11.3 IPS |
|
|
Style Transfer (Q)
|
98% |
20260
26.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2389
88.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1594
58.9 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4484
166.0 IPS |
|
|
Text Classification (SP)
|
100% |
1261
1.68 KIPS |
|
|
Text Classification (HP)
|
100% |
535
713.7 IPS |
|
|
Text Classification (Q)
|
97% |
1300
1.74 KIPS |
|
|
Machine Translation (SP)
|
100% |
1975
34.0 IPS |
|
|
Machine Translation (HP)
|
100% |
891
15.3 IPS |
|
|
Machine Translation (Q)
|
65% |
2532
50.9 IPS |
