JGINYUE B550M GAMING ARGB
Geekbench AI Score
3420
Single Precision Score
1294
Half Precision Score
4052
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| Upload Date | July 15 2025 11:04 AM |
| Views | 5 |
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% |
2886
536.8 IPS |
|
|
Image Classification (HP)
|
100% |
428
79.6 IPS |
|
|
Image Classification (Q)
|
96% |
3876
723.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
855
13.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
513
8.32 IPS |
|
|
Image Segmentation (Q)
|
97% |
2204
35.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
11254
13.1 IPS |
|
|
Pose Estimation (HP)
|
100% |
6632
7.74 IPS |
|
|
Pose Estimation (Q)
|
86% |
11229
13.3 IPS |
|
|
Object Detection (SP)
|
100% |
2827
224.2 IPS |
|
|
Object Detection (HP)
|
100% |
561
44.5 IPS |
|
|
Object Detection (Q)
|
58% |
2939
321.1 IPS |
|
|
Face Detection (SP)
|
100% |
4523
53.7 IPS |
|
|
Face Detection (HP)
|
100% |
1205
14.3 IPS |
|
|
Face Detection (Q)
|
96% |
7374
88.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
8292
63.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
1998
15.4 IPS |
|
|
Depth Estimation (Q)
|
78% |
9858
78.7 IPS |
|
|
Style Transfer (SP)
|
100% |
20907
26.9 IPS |
|
|
Style Transfer (HP)
|
100% |
17218
22.1 IPS |
|
|
Style Transfer (Q)
|
87% |
15053
19.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2188
80.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1610
59.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2004
74.2 IPS |
|
|
Text Classification (SP)
|
100% |
1011
1.35 KIPS |
|
|
Text Classification (HP)
|
100% |
461
615.9 IPS |
|
|
Text Classification (Q)
|
97% |
885
1.19 KIPS |
|
|
Machine Translation (SP)
|
100% |
1609
27.7 IPS |
|
|
Machine Translation (HP)
|
100% |
525
9.05 IPS |
|
|
Machine Translation (Q)
|
68% |
2186
42.2 IPS |
