Acer Swift SFG16-72
Geekbench AI Score
7650
Single Precision Score
12521
Half Precision Score
19597
Quantized Score
Geekbench AI 1.5.0 for Windows AVX2
Result Information
| User | Speedmoonday |
| Upload Date | October 09 2025 10:43 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | GPU |
| Device | Intel(R) Arc(TM) Graphics (iGPU) |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Famille (64-bit) |
| Model | Acer Swift SFG16-72 |
| Motherboard | MTL Pipefish_MTH |
| Power Plan | Acer |
| CPU Information | |
|---|---|
| Name | Intel Core Ultra 9 185H |
| Topology | 1 Processor, 16 Cores, 22 Threads |
| Identifier | GenuineIntel Family 6 Model 170 Stepping 4 |
| Base Frequency | 2.30 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 10 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
5456
1.01 KIPS |
|
|
Image Classification (HP)
|
100% |
8432
1.57 KIPS |
|
|
Image Classification (Q)
|
100% |
9968
1.85 KIPS |
|
|
Image Segmentation (SP)
|
100% |
4015
65.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
10818
175.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
16601
269.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
22926
26.8 IPS |
|
|
Pose Estimation (HP)
|
99% |
22678
26.5 IPS |
|
|
Pose Estimation (Q)
|
97% |
81362
95.3 IPS |
|
|
Object Detection (SP)
|
100% |
5176
410.6 IPS |
|
|
Object Detection (HP)
|
100% |
8671
687.8 IPS |
|
|
Object Detection (Q)
|
88% |
12679
1.02 KIPS |
|
|
Face Detection (SP)
|
100% |
8079
96.0 IPS |
|
|
Face Detection (HP)
|
100% |
16769
199.3 IPS |
|
|
Face Detection (Q)
|
100% |
30147
358.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
17184
132.4 IPS |
|
|
Depth Estimation (HP)
|
98% |
30778
237.9 IPS |
|
|
Depth Estimation (Q)
|
89% |
38130
296.4 IPS |
|
|
Style Transfer (SP)
|
100% |
54551
70.1 IPS |
|
|
Style Transfer (HP)
|
100% |
70418
90.5 IPS |
|
|
Style Transfer (Q)
|
98% |
178982
230.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
9087
335.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
16040
592.3 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
23204
859.3 IPS |
|
|
Text Classification (SP)
|
71% |
1610
2.33 KIPS |
|
|
Text Classification (HP)
|
71% |
2625
3.80 KIPS |
|
|
Text Classification (Q)
|
92% |
2807
3.77 KIPS |
|
|
Machine Translation (SP)
|
100% |
2385
41.1 IPS |
|
|
Machine Translation (HP)
|
98% |
3451
59.6 IPS |
|
|
Machine Translation (Q)
|
98% |
3652
63.1 IPS |
