Acer Swift SFG14-73T
Geekbench AI Score
2697
Single Precision Score
9051
Half Precision Score
14020
Quantized Score
Geekbench AI 1.5.0 for Windows AVX2
Result Information
| Upload Date | September 17 2025 07:18 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | NPU |
| Device | Intel(R) AI Boost |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home Single Language (64-bit) |
| Model | Acer Swift SFG14-73T |
| Motherboard | MTL Goldfish_MTH |
| Power Plan | Acer |
| CPU Information | |
|---|---|
| Name | Intel Core Ultra 7 155H |
| Topology | 1 Processor, 16 Cores, 22 Threads |
| Identifier | GenuineIntel Family 6 Model 170 Stepping 4 |
| Base Frequency | 1.40 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 10 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1445
268.7 IPS |
|
|
Image Classification (HP)
|
100% |
6254
1.16 KIPS |
|
|
Image Classification (Q)
|
100% |
8810
1.64 KIPS |
|
|
Image Segmentation (SP)
|
100% |
2199
35.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
2482
40.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
3137
50.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
3425
4.00 IPS |
|
|
Pose Estimation (HP)
|
100% |
30781
35.9 IPS |
|
|
Pose Estimation (Q)
|
96% |
65844
77.1 IPS |
|
|
Object Detection (SP)
|
100% |
1462
116.0 IPS |
|
|
Object Detection (HP)
|
100% |
5453
432.6 IPS |
|
|
Object Detection (Q)
|
88% |
9219
739.1 IPS |
|
|
Face Detection (SP)
|
100% |
4770
56.7 IPS |
|
|
Face Detection (HP)
|
100% |
15616
185.6 IPS |
|
|
Face Detection (Q)
|
100% |
29360
348.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
4164
32.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
17046
131.3 IPS |
|
|
Depth Estimation (Q)
|
88% |
31297
243.5 IPS |
|
|
Style Transfer (SP)
|
100% |
10574
13.6 IPS |
|
|
Style Transfer (HP)
|
100% |
48886
62.8 IPS |
|
|
Style Transfer (Q)
|
98% |
88122
113.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2017
74.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
14279
527.3 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
27482
1.02 KIPS |
|
|
Text Classification (SP)
|
100% |
1750
2.34 KIPS |
|
|
Text Classification (HP)
|
100% |
1869
2.49 KIPS |
|
|
Text Classification (Q)
|
92% |
1882
2.53 KIPS |
|
|
Machine Translation (SP)
|
100% |
1729
29.8 IPS |
|
|
Machine Translation (HP)
|
100% |
4078
70.2 IPS |
|
|
Machine Translation (Q)
|
100% |
4179
72.0 IPS |
