Acer Swift SF14-51
Geekbench AI Score
2260
Single Precision Score
1235
Half Precision Score
3789
Quantized Score
Geekbench AI 1.1.0 for Windows AVX2
Result Information
| Upload Date | November 20 2024 11:38 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel(R) Core(TM) Ultra 7 258V |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | Acer Swift SF14-51 |
| 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% |
1338
248.7 IPS |
|
|
Image Classification (HP)
|
100% |
503
93.6 IPS |
|
|
Image Classification (Q)
|
99% |
2674
498.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
1328
21.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
883
14.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
2417
39.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
3128
3.65 IPS |
|
|
Pose Estimation (HP)
|
100% |
2602
3.04 IPS |
|
|
Pose Estimation (Q)
|
95% |
11788
13.8 IPS |
|
|
Object Detection (SP)
|
100% |
1474
116.9 IPS |
|
|
Object Detection (HP)
|
100% |
587
46.5 IPS |
|
|
Object Detection (Q)
|
88% |
1571
125.9 IPS |
|
|
Face Detection (SP)
|
100% |
3173
37.7 IPS |
|
|
Face Detection (HP)
|
100% |
1497
17.8 IPS |
|
|
Face Detection (Q)
|
97% |
3848
45.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
4110
31.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
1848
14.2 IPS |
|
|
Depth Estimation (Q)
|
77% |
6297
50.4 IPS |
|
|
Style Transfer (SP)
|
100% |
7884
10.1 IPS |
|
|
Style Transfer (HP)
|
100% |
6499
8.35 IPS |
|
|
Style Transfer (Q)
|
98% |
16658
21.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1667
61.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1436
53.0 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
3571
132.2 IPS |
|
|
Text Classification (SP)
|
100% |
1294
1.73 KIPS |
|
|
Text Classification (HP)
|
100% |
639
852.7 IPS |
|
|
Text Classification (Q)
|
97% |
1598
2.14 KIPS |
|
|
Machine Translation (SP)
|
100% |
1917
33.0 IPS |
|
|
Machine Translation (HP)
|
100% |
739
12.7 IPS |
|
|
Machine Translation (Q)
|
60% |
2215
49.4 IPS |
