Acer Swift SFE14-51T Windows11 OpenVINO GPU Acer Swift SFE14-51T
Geekbench AI Score
10642
Single Precision Score
26371
Half Precision Score
31035
Quantized Score
Geekbench AI 1.7.0 for Windows AVX2
Result Information
| User | diegotomc |
| Upload Date | March 27 2026 03:22 AM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | GPU |
| Device | Intel(R) Arc(TM) 140V GPU (16GB) (iGPU) |
| 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% |
7384
1.37 KIPS |
|
|
Image Classification (HP)
|
100% |
14030
2.61 KIPS |
|
|
Image Classification (Q)
|
100% |
17666
3.29 KIPS |
|
|
Image Segmentation (SP)
|
100% |
9968
161.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
27464
445.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
32413
525.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
24186
28.2 IPS |
|
|
Pose Estimation (HP)
|
100% |
143890
167.9 IPS |
|
|
Pose Estimation (Q)
|
97% |
275720
322.8 IPS |
|
|
Object Detection (SP)
|
100% |
6417
509.0 IPS |
|
|
Object Detection (HP)
|
100% |
16155
1.28 KIPS |
|
|
Object Detection (Q)
|
88% |
21035
1.69 KIPS |
|
|
Face Detection (SP)
|
100% |
13199
156.8 IPS |
|
|
Face Detection (HP)
|
100% |
32827
390.1 IPS |
|
|
Face Detection (Q)
|
100% |
46855
556.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
25187
194.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
63438
488.8 IPS |
|
|
Depth Estimation (Q)
|
89% |
67875
527.8 IPS |
|
|
Style Transfer (SP)
|
100% |
59572
76.6 IPS |
|
|
Style Transfer (HP)
|
100% |
212007
272.5 IPS |
|
|
Style Transfer (Q)
|
98% |
296503
382.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
9918
366.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34635
1.28 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
36039
1.33 KIPS |
|
|
Text Classification (SP)
|
100% |
2780
3.71 KIPS |
|
|
Text Classification (HP)
|
100% |
2736
3.65 KIPS |
|
|
Text Classification (Q)
|
92% |
1796
2.41 KIPS |
|
|
Machine Translation (SP)
|
100% |
2989
51.5 IPS |
|
|
Machine Translation (HP)
|
98% |
4342
75.0 IPS |
|
|
Machine Translation (Q)
|
100% |
4090
70.4 IPS |
