Acer Swift SFG14-72
Geekbench AI Score
1585
Single Precision Score
1638
Half Precision Score
1121
Quantized Score
Geekbench AI 1.0.0 for Linux AVX2
Result Information
| User | ciassoc |
| Upload Date | August 16 2024 08:40 AM |
| Views | 4 |
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% |
1050
195.4 IPS |
|
|
Image Classification (HP)
|
100% |
1169
217.5 IPS |
|
|
Image Classification (Q)
|
99% |
790
147.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
1669
27.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
1659
26.9 IPS |
|
|
Image Segmentation (Q)
|
98% |
853
13.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
2054
2.40 IPS |
|
|
Pose Estimation (HP)
|
100% |
2067
2.41 IPS |
|
|
Pose Estimation (Q)
|
96% |
2421
2.84 IPS |
|
|
Object Detection (SP)
|
100% |
1090
86.5 IPS |
|
|
Object Detection (HP)
|
100% |
1173
93.0 IPS |
|
|
Object Detection (Q)
|
86% |
835
67.2 IPS |
|
|
Face Detection (SP)
|
100% |
2379
28.3 IPS |
|
|
Face Detection (HP)
|
100% |
2411
28.7 IPS |
|
|
Face Detection (Q)
|
97% |
1740
20.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
2128
16.4 IPS |
|
|
Depth Estimation (HP)
|
100% |
2099
16.2 IPS |
|
|
Depth Estimation (Q)
|
74% |
1753
14.2 IPS |
|
|
Style Transfer (SP)
|
100% |
3044
3.91 IPS |
|
|
Style Transfer (HP)
|
100% |
3050
3.92 IPS |
|
|
Style Transfer (Q)
|
98% |
4713
6.08 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1370
50.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1359
50.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1130
41.9 IPS |
|
|
Text Classification (SP)
|
100% |
807
1.08 KIPS |
|
|
Text Classification (HP)
|
100% |
813
1.08 KIPS |
|
|
Text Classification (Q)
|
92% |
333
447.0 IPS |
|
|
Machine Translation (SP)
|
100% |
1504
25.9 IPS |
|
|
Machine Translation (HP)
|
100% |
1736
29.9 IPS |
|
|
Machine Translation (Q)
|
58% |
426
10.0 IPS |
