QEMU Standard PC (Q35 + ICH9, 2009)
Geekbench AI Score
3600
Single Precision Score
3689
Half Precision Score
2531
Quantized Score
Geekbench AI 1.4.0 for Linux AVX2
Result Information
| User | ccebelenski |
| Upload Date | July 08 2025 10:51 PM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Intel(R) Core(TM) Ultra 9 285K |
| System Information | |
|---|---|
| Operating System | Fedora Linux 42 (Workstation Edition) |
| Model | QEMU Standard PC (Q35 + ICH9, 2009) |
| Motherboard | N/A |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 9 285K |
| Topology | 1 Processor, 24 Cores |
| Identifier | GenuineIntel Family 6 Model 198 Stepping 2 |
| Base Frequency | 3.69 GHz |
| Cluster 1 | 0 Cores |
| Memory Information | |
|---|---|
| Size | 62.76 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2617
486.7 IPS |
|
|
Image Classification (HP)
|
100% |
2800
520.7 IPS |
|
|
Image Classification (Q)
|
99% |
1899
354.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
3735
60.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
4313
69.9 IPS |
|
|
Image Segmentation (Q)
|
98% |
1777
28.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
4665
5.44 IPS |
|
|
Pose Estimation (HP)
|
100% |
4599
5.37 IPS |
|
|
Pose Estimation (Q)
|
96% |
6819
7.99 IPS |
|
|
Object Detection (SP)
|
100% |
2700
214.2 IPS |
|
|
Object Detection (HP)
|
100% |
2905
230.5 IPS |
|
|
Object Detection (Q)
|
85% |
1870
150.5 IPS |
|
|
Face Detection (SP)
|
100% |
5190
61.7 IPS |
|
|
Face Detection (HP)
|
100% |
5343
63.5 IPS |
|
|
Face Detection (Q)
|
97% |
3946
47.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
4262
32.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
4190
32.3 IPS |
|
|
Depth Estimation (Q)
|
63% |
3211
30.1 IPS |
|
|
Style Transfer (SP)
|
100% |
4765
6.13 IPS |
|
|
Style Transfer (HP)
|
100% |
4819
6.20 IPS |
|
|
Style Transfer (Q)
|
98% |
8752
11.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3112
114.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
3170
117.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2635
97.6 IPS |
|
|
Text Classification (SP)
|
100% |
2169
2.90 KIPS |
|
|
Text Classification (HP)
|
100% |
2168
2.89 KIPS |
|
|
Text Classification (Q)
|
92% |
1077
1.45 KIPS |
|
|
Machine Translation (SP)
|
100% |
4179
72.0 IPS |
|
|
Machine Translation (HP)
|
100% |
3907
67.3 IPS |
|
|
Machine Translation (Q)
|
58% |
797
18.7 IPS |
