Acer Swift SFG14-72
Geekbench AI Score
1733
Single Precision Score
516
Half Precision Score
3405
Quantized Score
Geekbench AI 1.0.0 for Linux AVX2
Result Information
| User | ciassoc |
| Upload Date | August 16 2024 10:41 AM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel Core Ultra 7 155H |
| System Information | |
|---|---|
| Operating System | openSUSE Tumbleweed |
| Model | Acer Swift SFG14-72 |
| Motherboard | MTL Coral_MTH |
| 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 | 4.80 GHz |
| Cluster 1 | 0 Cores |
| Memory Information | |
|---|---|
| Size | 31.01 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
952
177.1 IPS |
|
|
Image Classification (HP)
|
100% |
115
21.4 IPS |
|
|
Image Classification (Q)
|
97% |
2480
462.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
884
14.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
186
3.01 IPS |
|
|
Image Segmentation (Q)
|
99% |
2243
36.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
2855
3.33 IPS |
|
|
Pose Estimation (HP)
|
100% |
2312
2.70 IPS |
|
|
Pose Estimation (Q)
|
95% |
14941
17.5 IPS |
|
|
Object Detection (SP)
|
100% |
1121
88.9 IPS |
|
|
Object Detection (HP)
|
100% |
150
11.9 IPS |
|
|
Object Detection (Q)
|
88% |
1343
107.6 IPS |
|
|
Face Detection (SP)
|
100% |
2372
28.2 IPS |
|
|
Face Detection (HP)
|
100% |
349
4.15 IPS |
|
|
Face Detection (Q)
|
97% |
3866
46.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
3441
26.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
844
6.51 IPS |
|
|
Depth Estimation (Q)
|
76% |
6774
54.6 IPS |
|
|
Style Transfer (SP)
|
100% |
7369
9.47 IPS |
|
|
Style Transfer (HP)
|
100% |
5864
7.54 IPS |
|
|
Style Transfer (Q)
|
98% |
16722
21.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1443
53.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1078
39.8 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
2614
96.8 IPS |
|
|
Text Classification (SP)
|
100% |
844
1.13 KIPS |
|
|
Text Classification (HP)
|
100% |
311
415.5 IPS |
|
|
Text Classification (Q)
|
97% |
1122
1.50 KIPS |
|
|
Machine Translation (SP)
|
100% |
1239
21.3 IPS |
|
|
Machine Translation (HP)
|
100% |
312
5.38 IPS |
|
|
Machine Translation (Q)
|
60% |
1464
32.7 IPS |
