B450M Pro4-F
Geekbench AI Score
1417
Single Precision Score
776
Half Precision Score
1191
Quantized Score
Geekbench AI 1.6.0 for Windows AVX2
Result Information
| User | Blondin |
| Upload Date | March 09 2026 05:04 PM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | AMD Ryzen 3 1200 |
| System Information | |
|---|---|
| Operating System | Windows 10 (64-bit) |
| Model | B450M Pro4-F |
| Motherboard | ASRock B450M Pro4-F |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 3 1200 |
| Topology | 1 Processor, 4 Cores |
| Identifier | AuthenticAMD Family 23 Model 1 Stepping 1 |
| Base Frequency | 4.15 GHz |
| Cluster 1 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
988
183.7 IPS |
|
|
Image Classification (HP)
|
100% |
335
62.4 IPS |
|
|
Image Classification (Q)
|
96% |
906
169.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
650
10.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
385
6.24 IPS |
|
|
Image Segmentation (Q)
|
97% |
919
15.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
1817
2.12 IPS |
|
|
Pose Estimation (HP)
|
100% |
1591
1.86 IPS |
|
|
Pose Estimation (Q)
|
86% |
1728
2.04 IPS |
|
|
Object Detection (SP)
|
100% |
957
75.9 IPS |
|
|
Object Detection (HP)
|
100% |
407
32.2 IPS |
|
|
Object Detection (Q)
|
58% |
617
67.4 IPS |
|
|
Face Detection (SP)
|
100% |
2717
32.3 IPS |
|
|
Face Detection (HP)
|
100% |
963
11.4 IPS |
|
|
Face Detection (Q)
|
96% |
2360
28.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
2512
19.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
1146
8.83 IPS |
|
|
Depth Estimation (Q)
|
78% |
2226
17.8 IPS |
|
|
Style Transfer (SP)
|
100% |
4815
6.19 IPS |
|
|
Style Transfer (HP)
|
100% |
4103
5.27 IPS |
|
|
Style Transfer (Q)
|
87% |
4410
5.74 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
916
33.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
837
30.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
907
33.6 IPS |
|
|
Text Classification (SP)
|
100% |
816
1.09 KIPS |
|
|
Text Classification (HP)
|
100% |
428
571.3 IPS |
|
|
Text Classification (Q)
|
97% |
292
391.1 IPS |
|
|
Machine Translation (SP)
|
100% |
1192
20.5 IPS |
|
|
Machine Translation (HP)
|
100% |
585
10.1 IPS |
|
|
Machine Translation (Q)
|
68% |
1063
20.5 IPS |
