Acer Swift SFG14-72
Geekbench AI Score
8021
Single Precision Score
13036
Half Precision Score
19700
Quantized Score
Geekbench AI 1.5.0 for Linux AVX2
Result Information
| User | ciassoc |
| Upload Date | February 20 2026 11:11 AM |
| Views | 10 |
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% |
6239
1.16 KIPS |
|
|
Image Classification (HP)
|
100% |
8822
1.64 KIPS |
|
|
Image Classification (Q)
|
100% |
10334
1.92 KIPS |
|
|
Image Segmentation (SP)
|
100% |
4832
78.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
12676
205.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
18557
301.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
22909
26.7 IPS |
|
|
Pose Estimation (HP)
|
99% |
21593
25.3 IPS |
|
|
Pose Estimation (Q)
|
97% |
75593
88.5 IPS |
|
|
Object Detection (SP)
|
100% |
4640
368.0 IPS |
|
|
Object Detection (HP)
|
100% |
8946
709.6 IPS |
|
|
Object Detection (Q)
|
88% |
12874
1.03 KIPS |
|
|
Face Detection (SP)
|
100% |
9744
115.8 IPS |
|
|
Face Detection (HP)
|
100% |
20297
241.2 IPS |
|
|
Face Detection (Q)
|
100% |
34355
408.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
16134
124.3 IPS |
|
|
Depth Estimation (HP)
|
98% |
29225
225.9 IPS |
|
|
Depth Estimation (Q)
|
89% |
33950
263.9 IPS |
|
|
Style Transfer (SP)
|
100% |
57599
74.0 IPS |
|
|
Style Transfer (HP)
|
100% |
71412
91.8 IPS |
|
|
Style Transfer (Q)
|
98% |
185035
238.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
9832
363.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
16465
608.0 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
22789
843.9 IPS |
|
|
Text Classification (SP)
|
71% |
1427
2.06 KIPS |
|
|
Text Classification (HP)
|
71% |
2526
3.65 KIPS |
|
|
Text Classification (Q)
|
92% |
2582
3.47 KIPS |
|
|
Machine Translation (SP)
|
100% |
2710
46.7 IPS |
|
|
Machine Translation (HP)
|
98% |
3724
64.4 IPS |
|
|
Machine Translation (Q)
|
98% |
3715
64.2 IPS |
