Acer Swift SFG14-72
Geekbench AI Score
6106
Single Precision Score
8487
Half Precision Score
11494
Quantized Score
Geekbench AI 1.0.0 for Linux AVX2
Result Information
| User | ciassoc |
| Upload Date | August 16 2024 10:27 AM |
| Views | 13 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | GPU |
| Device | Intel(R) Arc(TM) Graphics (iGPU) |
| 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% |
3731
693.9 IPS |
|
|
Image Classification (HP)
|
100% |
4787
890.2 IPS |
|
|
Image Classification (Q)
|
100% |
5034
936.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
3849
62.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
8402
136.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
10564
171.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
22676
26.5 IPS |
|
|
Pose Estimation (HP)
|
99% |
20964
24.5 IPS |
|
|
Pose Estimation (Q)
|
97% |
62200
72.8 IPS |
|
|
Object Detection (SP)
|
100% |
3663
290.5 IPS |
|
|
Object Detection (HP)
|
100% |
5025
398.6 IPS |
|
|
Object Detection (Q)
|
88% |
6045
484.4 IPS |
|
|
Face Detection (SP)
|
100% |
8103
96.3 IPS |
|
|
Face Detection (HP)
|
100% |
13177
156.6 IPS |
|
|
Face Detection (Q)
|
100% |
20324
241.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
15129
116.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
23830
184.1 IPS |
|
|
Depth Estimation (Q)
|
79% |
26294
208.7 IPS |
|
|
Style Transfer (SP)
|
100% |
54076
69.5 IPS |
|
|
Style Transfer (HP)
|
100% |
66116
85.0 IPS |
|
|
Style Transfer (Q)
|
98% |
152681
196.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
7835
289.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
11666
430.8 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
15401
570.4 IPS |
|
|
Text Classification (SP)
|
71% |
884
1.28 KIPS |
|
|
Text Classification (HP)
|
71% |
1128
1.63 KIPS |
|
|
Text Classification (Q)
|
92% |
1085
1.46 KIPS |
|
|
Machine Translation (SP)
|
100% |
1317
22.7 IPS |
|
|
Machine Translation (HP)
|
96% |
1675
29.0 IPS |
|
|
Machine Translation (Q)
|
89% |
1477
25.7 IPS |
