Acer Swift SFG14-72
Geekbench AI Score
8195
Single Precision Score
13181
Half Precision Score
19739
Quantized Score
Geekbench AI 1.7.0 for Linux AVX2
Result Information
| User | ciassoc |
| Upload Date | March 10 2026 11:00 AM |
| Views | 6 |
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% |
6291
1.17 KIPS |
|
|
Image Classification (HP)
|
100% |
8798
1.64 KIPS |
|
|
Image Classification (Q)
|
100% |
10320
1.92 KIPS |
|
|
Image Segmentation (SP)
|
100% |
4826
78.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
12647
205.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
18565
301.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
22343
26.1 IPS |
|
|
Pose Estimation (HP)
|
99% |
21286
24.9 IPS |
|
|
Pose Estimation (Q)
|
97% |
75196
88.0 IPS |
|
|
Object Detection (SP)
|
100% |
4636
367.7 IPS |
|
|
Object Detection (HP)
|
100% |
8787
697.0 IPS |
|
|
Object Detection (Q)
|
88% |
12822
1.03 KIPS |
|
|
Face Detection (SP)
|
100% |
9609
114.2 IPS |
|
|
Face Detection (HP)
|
100% |
20485
243.4 IPS |
|
|
Face Detection (Q)
|
100% |
34475
409.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
16429
126.6 IPS |
|
|
Depth Estimation (HP)
|
98% |
28057
216.8 IPS |
|
|
Depth Estimation (Q)
|
89% |
34494
268.1 IPS |
|
|
Style Transfer (SP)
|
100% |
58030
74.6 IPS |
|
|
Style Transfer (HP)
|
100% |
69665
89.6 IPS |
|
|
Style Transfer (Q)
|
98% |
190524
245.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
9961
367.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
16647
614.7 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
22327
826.9 IPS |
|
|
Text Classification (SP)
|
71% |
1548
2.24 KIPS |
|
|
Text Classification (HP)
|
71% |
3094
4.47 KIPS |
|
|
Text Classification (Q)
|
92% |
2597
3.49 KIPS |
|
|
Machine Translation (SP)
|
100% |
3076
53.0 IPS |
|
|
Machine Translation (HP)
|
98% |
3691
63.8 IPS |
|
|
Machine Translation (Q)
|
98% |
3702
64.0 IPS |
