JGINYUE B550M GAMING ARGB
Geekbench AI Score
3417
Single Precision Score
1305
Half Precision Score
4057
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| Upload Date | July 15 2025 11:00 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | AMD Ryzen 9 3950X |
| System Information | |
|---|---|
| Operating System | Windows 11 Pro (64-bit) |
| Model | JGINYUE B550M GAMING ARGB |
| Motherboard | JGINYUE B550M GAMING ARGB |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 9 3950X |
| Topology | 1 Processor, 16 Cores, 32 Threads |
| Identifier | AuthenticAMD Family 23 Model 113 Stepping 0 |
| Base Frequency | 4.25 GHz |
| Cluster 1 | 16 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2752
511.7 IPS |
|
|
Image Classification (HP)
|
100% |
426
79.2 IPS |
|
|
Image Classification (Q)
|
96% |
3913
730.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
899
14.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
523
8.48 IPS |
|
|
Image Segmentation (Q)
|
97% |
2234
36.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
11368
13.3 IPS |
|
|
Pose Estimation (HP)
|
100% |
6631
7.74 IPS |
|
|
Pose Estimation (Q)
|
86% |
11109
13.1 IPS |
|
|
Object Detection (SP)
|
100% |
2826
224.2 IPS |
|
|
Object Detection (HP)
|
100% |
561
44.5 IPS |
|
|
Object Detection (Q)
|
58% |
2895
316.3 IPS |
|
|
Face Detection (SP)
|
100% |
4353
51.7 IPS |
|
|
Face Detection (HP)
|
100% |
1188
14.1 IPS |
|
|
Face Detection (Q)
|
96% |
7474
89.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
8693
67.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
2014
15.5 IPS |
|
|
Depth Estimation (Q)
|
78% |
9989
79.7 IPS |
|
|
Style Transfer (SP)
|
100% |
21023
27.0 IPS |
|
|
Style Transfer (HP)
|
100% |
18566
23.9 IPS |
|
|
Style Transfer (Q)
|
87% |
15068
19.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2171
80.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1605
59.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2001
74.1 IPS |
|
|
Text Classification (SP)
|
100% |
997
1.33 KIPS |
|
|
Text Classification (HP)
|
100% |
465
620.1 IPS |
|
|
Text Classification (Q)
|
97% |
892
1.20 KIPS |
|
|
Machine Translation (SP)
|
100% |
1587
27.3 IPS |
|
|
Machine Translation (HP)
|
100% |
524
9.03 IPS |
|
|
Machine Translation (Q)
|
68% |
2142
41.4 IPS |
