Acer Swift SF14-51T
Geekbench AI Score
2356
Single Precision Score
2354
Half Precision Score
5742
Quantized Score
Geekbench AI 1.1.0 for Windows AVX2
Result Information
| Upload Date | November 06 2024 07:42 PM |
| Views | 10 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | CPU |
| Device | Intel(R) Core(TM) Ultra 7 258V |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | Acer Swift SF14-51T |
| Motherboard | LNL Icefish_LNV |
| Power Plan | Acer |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 7 258V |
| Topology | 1 Processor, 8 Cores |
| Identifier | GenuineIntel Family 6 Model 189 Stepping 1 |
| Base Frequency | 2.20 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1464
272.2 IPS |
|
|
Image Classification (HP)
|
100% |
1529
284.3 IPS |
|
|
Image Classification (Q)
|
100% |
3947
734.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
1435
23.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
1461
23.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
2636
42.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
2653
3.10 IPS |
|
|
Pose Estimation (HP)
|
100% |
2659
3.10 IPS |
|
|
Pose Estimation (Q)
|
96% |
10097
11.8 IPS |
|
|
Object Detection (SP)
|
100% |
1477
117.2 IPS |
|
|
Object Detection (HP)
|
100% |
1481
117.5 IPS |
|
|
Object Detection (Q)
|
88% |
3978
318.9 IPS |
|
|
Face Detection (SP)
|
100% |
4338
51.5 IPS |
|
|
Face Detection (HP)
|
100% |
4285
50.9 IPS |
|
|
Face Detection (Q)
|
100% |
10036
119.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
3749
28.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
3771
29.0 IPS |
|
|
Depth Estimation (Q)
|
89% |
10568
82.2 IPS |
|
|
Style Transfer (SP)
|
100% |
7892
10.1 IPS |
|
|
Style Transfer (HP)
|
100% |
7954
10.2 IPS |
|
|
Style Transfer (Q)
|
98% |
28852
37.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1662
61.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1665
61.5 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
5808
215.1 IPS |
|
|
Text Classification (SP)
|
100% |
1468
1.96 KIPS |
|
|
Text Classification (HP)
|
100% |
1446
1.93 KIPS |
|
|
Text Classification (Q)
|
92% |
2745
3.69 KIPS |
|
|
Machine Translation (SP)
|
100% |
2050
35.3 IPS |
|
|
Machine Translation (HP)
|
100% |
1924
33.1 IPS |
|
|
Machine Translation (Q)
|
100% |
1913
33.0 IPS |
