Acer Swift SFG14-72
Geekbench AI Score
1636
Single Precision Score
1603
Half Precision Score
1093
Quantized Score
Geekbench AI 1.0.0 for Linux AVX2
Result Information
| Upload Date | September 17 2024 09:21 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| 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% |
1107
205.8 IPS |
|
|
Image Classification (HP)
|
100% |
1114
207.1 IPS |
|
|
Image Classification (Q)
|
99% |
663
123.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
1648
26.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
1643
26.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
803
13.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
2032
2.37 IPS |
|
|
Pose Estimation (HP)
|
100% |
2052
2.39 IPS |
|
|
Pose Estimation (Q)
|
96% |
2407
2.82 IPS |
|
|
Object Detection (SP)
|
100% |
1137
90.1 IPS |
|
|
Object Detection (HP)
|
100% |
1221
96.8 IPS |
|
|
Object Detection (Q)
|
86% |
840
67.6 IPS |
|
|
Face Detection (SP)
|
100% |
2421
28.8 IPS |
|
|
Face Detection (HP)
|
100% |
2408
28.6 IPS |
|
|
Face Detection (Q)
|
97% |
1751
20.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
2100
16.2 IPS |
|
|
Depth Estimation (HP)
|
100% |
2137
16.5 IPS |
|
|
Depth Estimation (Q)
|
74% |
1750
14.2 IPS |
|
|
Style Transfer (SP)
|
100% |
2995
3.85 IPS |
|
|
Style Transfer (HP)
|
100% |
3030
3.90 IPS |
|
|
Style Transfer (Q)
|
98% |
4690
6.05 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1380
51.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1382
51.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1121
41.5 IPS |
|
|
Text Classification (SP)
|
100% |
913
1.22 KIPS |
|
|
Text Classification (HP)
|
100% |
782
1.04 KIPS |
|
|
Text Classification (Q)
|
92% |
316
424.7 IPS |
|
|
Machine Translation (SP)
|
100% |
1706
29.4 IPS |
|
|
Machine Translation (HP)
|
100% |
1452
25.0 IPS |
|
|
Machine Translation (Q)
|
58% |
447
10.5 IPS |
