QEMU Standard PC (Q35 + ICH9, 2009)
Geekbench AI Score
45247
Single Precision Score
66382
Half Precision Score
34050
Quantized Score
Geekbench AI 1.5.0 for Windows AVX2
Result Information
| User | Wint3rmu7e |
| Upload Date | October 29 2025 05:44 AM |
| Views | 14 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 5090 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | QEMU Standard PC (Q35 + ICH9, 2009) |
| Motherboard | |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 9 9950X |
| Topology | 1 Processor, 16 Cores |
| Identifier | AuthenticAMD Family 26 Model 68 Stepping 0 |
| Base Frequency | 4.29 GHz |
| Cluster 1 | 16 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
| Type | RAM |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
14622
2.72 KIPS |
|
|
Image Classification (HP)
|
100% |
18109
3.37 KIPS |
|
|
Image Classification (Q)
|
100% |
12880
2.40 KIPS |
|
|
Image Segmentation (SP)
|
100% |
38770
628.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
50304
815.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
35855
583.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
400941
467.8 IPS |
|
|
Pose Estimation (HP)
|
100% |
952996
1.11 KIPS |
|
|
Pose Estimation (Q)
|
96% |
324473
380.1 IPS |
|
|
Object Detection (SP)
|
100% |
23570
1.87 KIPS |
|
|
Object Detection (HP)
|
100% |
30631
2.43 KIPS |
|
|
Object Detection (Q)
|
85% |
19358
1.56 KIPS |
|
|
Face Detection (SP)
|
100% |
75342
895.2 IPS |
|
|
Face Detection (HP)
|
100% |
101632
1.21 KIPS |
|
|
Face Detection (Q)
|
97% |
60258
718.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
103298
795.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
178588
1.38 KIPS |
|
|
Depth Estimation (Q)
|
77% |
75127
601.7 IPS |
|
|
Style Transfer (SP)
|
100% |
590884
759.6 IPS |
|
|
Style Transfer (HP)
|
100% |
1607561
2.07 KIPS |
|
|
Style Transfer (Q)
|
98% |
497892
642.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
64867
2.40 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
82533
3.05 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
48622
1.80 KIPS |
|
|
Text Classification (SP)
|
100% |
3040
4.06 KIPS |
|
|
Text Classification (HP)
|
100% |
3478
4.64 KIPS |
|
|
Text Classification (Q)
|
97% |
2030
2.72 KIPS |
|
|
Machine Translation (SP)
|
100% |
7404
127.5 IPS |
|
|
Machine Translation (HP)
|
100% |
7461
128.5 IPS |
|
|
Machine Translation (Q)
|
70% |
3247
60.9 IPS |
