QEMU Standard PC (Q35 + ICH9, 2009)
Geekbench AI Score
284
Single Precision Score
285
Half Precision Score
267
Quantized Score
Geekbench AI 1.3.0 for Linux AVX2
Result Information
| Upload Date | April 10 2025 03:34 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | AMD EPYC-v4 Processor |
| System Information | |
|---|---|
| Operating System | Ubuntu 22.10 |
| Model | QEMU Standard PC (Q35 + ICH9, 2009) |
| Motherboard | N/A |
| CPU Information | |
|---|---|
| Name | AMD EPYC-v4 Processor |
| Topology | 1 Processor, 1 Core |
| Identifier | AuthenticAMD Family 23 Model 1 Stepping 2 |
| Base Frequency | 2.84 GHz |
| Cluster 1 | 0 Cores |
| Memory Information | |
|---|---|
| Size | 1.29 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
255
47.4 IPS |
|
|
Image Classification (HP)
|
100% |
258
47.9 IPS |
|
|
Image Classification (Q)
|
99% |
163
30.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
325
5.27 IPS |
|
|
Image Segmentation (HP)
|
100% |
328
5.32 IPS |
|
|
Image Segmentation (Q)
|
98% |
204
3.32 IPS |
|
|
Pose Estimation (SP)
|
100% |
173
0.20 IPS |
|
|
Pose Estimation (HP)
|
100% |
184
0.21 IPS |
|
|
Pose Estimation (Q)
|
96% |
314
0.37 IPS |
|
|
Object Detection (SP)
|
100% |
233
18.5 IPS |
|
|
Object Detection (HP)
|
100% |
234
18.6 IPS |
|
|
Object Detection (Q)
|
85% |
164
13.2 IPS |
|
|
Face Detection (SP)
|
100% |
597
7.10 IPS |
|
|
Face Detection (HP)
|
100% |
604
7.18 IPS |
|
|
Face Detection (Q)
|
97% |
435
5.18 IPS |
|
|
Depth Estimation (SP)
|
100% |
505
3.89 IPS |
|
|
Depth Estimation (HP)
|
99% |
497
3.83 IPS |
|
|
Depth Estimation (Q)
|
63% |
323
3.03 IPS |
|
|
Style Transfer (SP)
|
100% |
33
0.04 IPS |
|
|
Style Transfer (HP)
|
100% |
32
0.04 IPS |
|
|
Style Transfer (Q)
|
98% |
750
0.97 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
300
11.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
299
11.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
208
7.69 IPS |
|
|
Text Classification (SP)
|
100% |
510
680.9 IPS |
|
|
Text Classification (HP)
|
100% |
500
667.1 IPS |
|
|
Text Classification (Q)
|
92% |
222
297.6 IPS |
|
|
Machine Translation (SP)
|
100% |
674
11.6 IPS |
|
|
Machine Translation (HP)
|
100% |
686
11.8 IPS |
|
|
Machine Translation (Q)
|
58% |
227
5.33 IPS |
