Acer Swift SFG14-73
Geekbench AI Score
6425
Single Precision Score
10551
Half Precision Score
15743
Quantized Score
Geekbench AI 1.4.0 for Windows AVX2
Result Information
| Upload Date | August 28 2025 07:47 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | GPU |
| Device | Intel(R) Arc(TM) Pro Graphics (iGPU) |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home Single Language (64-bit) |
| Model | Acer Swift SFG14-73 |
| Motherboard | MTL Goldfish_MTH |
| Power Plan | Acer |
| CPU Information | |
|---|---|
| Name | Intel Core Ultra 5 125H |
| Topology | 1 Processor, 14 Cores, 18 Threads |
| Identifier | GenuineIntel Family 6 Model 170 Stepping 4 |
| Base Frequency | 1.20 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 10 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
5398
1.00 KIPS |
|
|
Image Classification (HP)
|
100% |
7542
1.40 KIPS |
|
|
Image Classification (Q)
|
100% |
8772
1.63 KIPS |
|
|
Image Segmentation (SP)
|
100% |
2683
43.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
11004
178.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
15992
259.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
18896
22.0 IPS |
|
|
Pose Estimation (HP)
|
99% |
17803
20.8 IPS |
|
|
Pose Estimation (Q)
|
97% |
36015
42.2 IPS |
|
|
Object Detection (SP)
|
100% |
4758
377.4 IPS |
|
|
Object Detection (HP)
|
100% |
7900
626.6 IPS |
|
|
Object Detection (Q)
|
88% |
11742
941.0 IPS |
|
|
Face Detection (SP)
|
100% |
9337
110.9 IPS |
|
|
Face Detection (HP)
|
100% |
18225
216.6 IPS |
|
|
Face Detection (Q)
|
100% |
28986
344.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
17452
134.5 IPS |
|
|
Depth Estimation (HP)
|
98% |
31606
244.3 IPS |
|
|
Depth Estimation (Q)
|
89% |
35256
274.0 IPS |
|
|
Style Transfer (SP)
|
100% |
31904
41.0 IPS |
|
|
Style Transfer (HP)
|
100% |
33366
42.9 IPS |
|
|
Style Transfer (Q)
|
98% |
154534
199.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
7478
276.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
14067
519.4 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
18040
668.1 IPS |
|
|
Text Classification (SP)
|
71% |
1117
1.62 KIPS |
|
|
Text Classification (HP)
|
71% |
1782
2.58 KIPS |
|
|
Text Classification (Q)
|
92% |
1784
2.40 KIPS |
|
|
Machine Translation (SP)
|
100% |
2122
36.6 IPS |
|
|
Machine Translation (HP)
|
98% |
3043
52.6 IPS |
|
|
Machine Translation (Q)
|
98% |
3103
53.6 IPS |
