Acer Swift Neo SFN14-54H
Geekbench AI Score
1343
Single Precision Score
676
Half Precision Score
2681
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| Upload Date | May 28 2025 07:49 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel(R) Core(TM) Ultra 5 115U |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home Single Language (64-bit) |
| Model | Acer Swift Neo SFN14-54H |
| Motherboard | Acer Swift Neo SFN14-54H |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 5 115U |
| Topology | 1 Processor, 8 Cores, 10 Threads |
| Identifier | GenuineIntel Family 6 Model 170 Stepping 4 |
| Base Frequency | 1.50 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 6 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
927
172.4 IPS |
|
|
Image Classification (HP)
|
100% |
267
49.7 IPS |
|
|
Image Classification (Q)
|
99% |
2075
386.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
560
9.07 IPS |
|
|
Image Segmentation (HP)
|
100% |
423
6.86 IPS |
|
|
Image Segmentation (Q)
|
98% |
1512
24.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
1933
2.25 IPS |
|
|
Pose Estimation (HP)
|
100% |
1556
1.82 IPS |
|
|
Pose Estimation (Q)
|
94% |
6952
8.15 IPS |
|
|
Object Detection (SP)
|
100% |
930
73.8 IPS |
|
|
Object Detection (HP)
|
100% |
321
25.5 IPS |
|
|
Object Detection (Q)
|
86% |
2079
167.1 IPS |
|
|
Face Detection (SP)
|
100% |
2544
30.2 IPS |
|
|
Face Detection (HP)
|
100% |
767
9.11 IPS |
|
|
Face Detection (Q)
|
97% |
3708
44.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
2523
19.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
989
7.62 IPS |
|
|
Depth Estimation (Q)
|
78% |
5849
46.7 IPS |
|
|
Style Transfer (SP)
|
100% |
4894
6.29 IPS |
|
|
Style Transfer (HP)
|
100% |
3732
4.80 IPS |
|
|
Style Transfer (Q)
|
98% |
9015
11.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
951
35.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
793
29.3 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
1730
64.0 IPS |
|
|
Text Classification (SP)
|
100% |
818
1.09 KIPS |
|
|
Text Classification (HP)
|
100% |
397
529.7 IPS |
|
|
Text Classification (Q)
|
97% |
974
1.30 KIPS |
|
|
Machine Translation (SP)
|
100% |
842
14.5 IPS |
|
|
Machine Translation (HP)
|
100% |
399
6.87 IPS |
|
|
Machine Translation (Q)
|
65% |
1289
25.9 IPS |
