Acer Swift SF14-51
Geekbench AI Score
9439
Single Precision Score
23949
Half Precision Score
28507
Quantized Score
Geekbench AI 1.1.0 for Windows AVX2
Result Information
| Upload Date | November 25 2024 09:56 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | GPU |
| Device | Intel(R) Arc(TM) 140V GPU (16GB) (iGPU) |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Acer Swift SF14-51 |
| Motherboard | LNL Icefish_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% |
6655
1.24 KIPS |
|
|
Image Classification (HP)
|
100% |
13279
2.47 KIPS |
|
|
Image Classification (Q)
|
100% |
16397
3.05 KIPS |
|
|
Image Segmentation (SP)
|
100% |
7425
120.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
13887
225.1 IPS |
|
|
Image Segmentation (Q)
|
99% |
15074
244.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
24792
28.9 IPS |
|
|
Pose Estimation (HP)
|
100% |
131538
153.5 IPS |
|
|
Pose Estimation (Q)
|
97% |
253269
296.5 IPS |
|
|
Object Detection (SP)
|
100% |
6241
495.1 IPS |
|
|
Object Detection (HP)
|
100% |
13054
1.04 KIPS |
|
|
Object Detection (Q)
|
88% |
14237
1.14 KIPS |
|
|
Face Detection (SP)
|
100% |
13780
163.7 IPS |
|
|
Face Detection (HP)
|
100% |
31338
372.4 IPS |
|
|
Face Detection (Q)
|
100% |
39795
472.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
23974
184.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
55414
426.9 IPS |
|
|
Depth Estimation (Q)
|
89% |
66944
520.6 IPS |
|
|
Style Transfer (SP)
|
100% |
54463
70.0 IPS |
|
|
Style Transfer (HP)
|
100% |
162266
208.6 IPS |
|
|
Style Transfer (Q)
|
98% |
190507
245.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
9910
365.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
26412
975.3 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
33747
1.25 KIPS |
|
|
Text Classification (SP)
|
100% |
2955
3.94 KIPS |
|
|
Text Classification (HP)
|
100% |
5214
6.96 KIPS |
|
|
Text Classification (Q)
|
92% |
4388
5.90 KIPS |
|
|
Machine Translation (SP)
|
100% |
1394
24.0 IPS |
|
|
Machine Translation (HP)
|
100% |
5052
87.0 IPS |
|
|
Machine Translation (Q)
|
100% |
5293
91.2 IPS |
