Acer Swift SFG14-72
Geekbench AI Score
8058
Single Precision Score
13129
Half Precision Score
19679
Quantized Score
Geekbench AI 1.5.0 for Linux AVX2
Result Information
| User | ciassoc |
| Upload Date | March 10 2026 10:46 AM |
| Views | 8 |
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% |
6259
1.16 KIPS |
|
|
Image Classification (HP)
|
100% |
8826
1.64 KIPS |
|
|
Image Classification (Q)
|
100% |
10367
1.93 KIPS |
|
|
Image Segmentation (SP)
|
100% |
4830
78.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
12618
204.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
18700
304.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
22307
26.0 IPS |
|
|
Pose Estimation (HP)
|
99% |
21463
25.1 IPS |
|
|
Pose Estimation (Q)
|
97% |
74645
87.4 IPS |
|
|
Object Detection (SP)
|
100% |
4693
372.2 IPS |
|
|
Object Detection (HP)
|
100% |
8965
711.1 IPS |
|
|
Object Detection (Q)
|
88% |
12850
1.03 KIPS |
|
|
Face Detection (SP)
|
100% |
9780
116.2 IPS |
|
|
Face Detection (HP)
|
100% |
20378
242.1 IPS |
|
|
Face Detection (Q)
|
100% |
34339
408.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
16379
126.2 IPS |
|
|
Depth Estimation (HP)
|
98% |
29363
226.9 IPS |
|
|
Depth Estimation (Q)
|
89% |
33710
262.0 IPS |
|
|
Style Transfer (SP)
|
100% |
56908
73.2 IPS |
|
|
Style Transfer (HP)
|
100% |
72477
93.2 IPS |
|
|
Style Transfer (Q)
|
98% |
184753
238.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
9930
366.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
16523
610.1 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
22735
842.0 IPS |
|
|
Text Classification (SP)
|
71% |
1486
2.15 KIPS |
|
|
Text Classification (HP)
|
71% |
2668
3.86 KIPS |
|
|
Text Classification (Q)
|
92% |
2610
3.51 KIPS |
|
|
Machine Translation (SP)
|
100% |
2712
46.7 IPS |
|
|
Machine Translation (HP)
|
98% |
3715
64.2 IPS |
|
|
Machine Translation (Q)
|
98% |
3692
63.8 IPS |
