QEMU Standard PC (Q35 + ICH9, 2009)
Geekbench AI Score
902
Single Precision Score
849
Half Precision Score
2845
Quantized Score
Geekbench AI 1.5.0 for Windows x86 (64-bit)
Result Information
| Upload Date | November 11 2025 02:15 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% |
1129
210.0 IPS |
|
|
Image Classification (HP)
|
100% |
1118
207.9 IPS |
|
|
Image Classification (Q)
|
100% |
2406
447.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
1171
19.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
1261
20.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
2201
35.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
1660
1.94 IPS |
|
|
Pose Estimation (HP)
|
100% |
1671
1.95 IPS |
|
|
Pose Estimation (Q)
|
94% |
4225
4.96 IPS |
|
|
Object Detection (SP)
|
100% |
909
72.1 IPS |
|
|
Object Detection (HP)
|
100% |
880
69.8 IPS |
|
|
Object Detection (Q)
|
87% |
1734
139.1 IPS |
|
|
Face Detection (SP)
|
100% |
5076
60.3 IPS |
|
|
Face Detection (HP)
|
100% |
3150
37.4 IPS |
|
|
Face Detection (Q)
|
97% |
8748
104.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
2300
17.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
2869
22.1 IPS |
|
|
Depth Estimation (Q)
|
81% |
6970
55.1 IPS |
|
|
Style Transfer (SP)
|
100% |
41
0.05 IPS |
|
|
Style Transfer (HP)
|
100% |
41
0.05 IPS |
|
|
Style Transfer (Q)
|
98% |
22708
29.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1451
53.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1127
41.6 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
2344
86.8 IPS |
|
|
Text Classification (SP)
|
100% |
248
330.8 IPS |
|
|
Text Classification (HP)
|
100% |
223
298.1 IPS |
|
|
Text Classification (Q)
|
91% |
239
320.8 IPS |
|
|
Machine Translation (SP)
|
100% |
1043
18.0 IPS |
|
|
Machine Translation (HP)
|
100% |
1016
17.5 IPS |
|
|
Machine Translation (Q)
|
100% |
1158
19.9 IPS |
