QEMU Standard PC (Q35 + ICH9, 2009)
Geekbench AI Score
808
Single Precision Score
801
Half Precision Score
2705
Quantized Score
Geekbench AI 1.5.0 for Windows x86 (64-bit)
Result Information
| Upload Date | November 10 2025 08:35 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | CPU |
| Device | QEMU Virtual CPU version 2.5+ |
| System Information | |
|---|---|
| Operating System | Microsoft Windows Server 2022 Standard (64-bit) |
| Model | QEMU Standard PC (Q35 + ICH9, 2009) |
| Motherboard | |
| CPU Information | |
|---|---|
| Name | QEMU Virtual CPU version 2.5+ |
| Topology | 1 Processor, 12 Cores |
| Identifier | GenuineIntel Family 15 Model 107 Stepping 1 |
| Base Frequency | 2.30 GHz |
| Cluster 1 | 12 Cores |
| Memory Information | |
|---|---|
| Size | 20.00 GB |
| Type | RAM |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
913
169.7 IPS |
|
|
Image Classification (HP)
|
100% |
879
163.5 IPS |
|
|
Image Classification (Q)
|
100% |
2254
419.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
1333
21.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
1212
19.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
3100
50.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
1619
1.89 IPS |
|
|
Pose Estimation (HP)
|
100% |
1609
1.88 IPS |
|
|
Pose Estimation (Q)
|
94% |
4120
4.83 IPS |
|
|
Object Detection (SP)
|
100% |
659
52.3 IPS |
|
|
Object Detection (HP)
|
100% |
849
67.3 IPS |
|
|
Object Detection (Q)
|
87% |
1620
129.9 IPS |
|
|
Face Detection (SP)
|
100% |
3668
43.6 IPS |
|
|
Face Detection (HP)
|
100% |
4012
47.7 IPS |
|
|
Face Detection (Q)
|
97% |
9087
108.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
2173
16.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
2099
16.2 IPS |
|
|
Depth Estimation (Q)
|
81% |
4600
36.3 IPS |
|
|
Style Transfer (SP)
|
100% |
41
0.05 IPS |
|
|
Style Transfer (HP)
|
100% |
41
0.05 IPS |
|
|
Style Transfer (Q)
|
98% |
14752
19.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1050
38.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1000
36.9 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
3010
111.5 IPS |
|
|
Text Classification (SP)
|
100% |
265
353.1 IPS |
|
|
Text Classification (HP)
|
100% |
250
334.2 IPS |
|
|
Text Classification (Q)
|
91% |
289
388.9 IPS |
|
|
Machine Translation (SP)
|
100% |
1005
17.3 IPS |
|
|
Machine Translation (HP)
|
100% |
873
15.0 IPS |
|
|
Machine Translation (Q)
|
100% |
841
14.5 IPS |
