Acer Swift SFG14-72
Geekbench AI Score
1763
Single Precision Score
546
Half Precision Score
3419
Quantized Score
Geekbench AI 1.0.0 for Linux AVX2
Result Information
| User | ciassoc |
| Upload Date | August 16 2024 10:10 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% |
983
182.8 IPS |
|
|
Image Classification (HP)
|
100% |
198
36.8 IPS |
|
|
Image Classification (Q)
|
97% |
2088
389.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
1043
16.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
180
2.92 IPS |
|
|
Image Segmentation (Q)
|
99% |
2090
34.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
2880
3.36 IPS |
|
|
Pose Estimation (HP)
|
100% |
2410
2.81 IPS |
|
|
Pose Estimation (Q)
|
95% |
14601
17.1 IPS |
|
|
Object Detection (SP)
|
100% |
1125
89.2 IPS |
|
|
Object Detection (HP)
|
100% |
246
19.5 IPS |
|
|
Object Detection (Q)
|
88% |
1126
90.2 IPS |
|
|
Face Detection (SP)
|
100% |
2403
28.6 IPS |
|
|
Face Detection (HP)
|
100% |
225
2.68 IPS |
|
|
Face Detection (Q)
|
97% |
3307
39.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
3385
26.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
654
5.04 IPS |
|
|
Depth Estimation (Q)
|
76% |
5729
46.2 IPS |
|
|
Style Transfer (SP)
|
100% |
7107
9.14 IPS |
|
|
Style Transfer (HP)
|
100% |
5892
7.57 IPS |
|
|
Style Transfer (Q)
|
98% |
20112
25.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1439
53.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1081
39.9 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
3222
119.3 IPS |
|
|
Text Classification (SP)
|
100% |
816
1.09 KIPS |
|
|
Text Classification (HP)
|
100% |
403
537.8 IPS |
|
|
Text Classification (Q)
|
97% |
1162
1.56 KIPS |
|
|
Machine Translation (SP)
|
100% |
1288
22.2 IPS |
|
|
Machine Translation (HP)
|
100% |
299
5.16 IPS |
|
|
Machine Translation (Q)
|
60% |
2133
47.6 IPS |
