B550M-ITX/ac
Geekbench AI Score
5299
Single Precision Score
5280
Half Precision Score
7999
Quantized Score
Geekbench AI 1.5.0 for Windows AVX2
Result Information
| User | kilio-silver |
| Upload Date | October 26 2025 02:19 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | CPU |
| Device | AMD Ryzen 7 5700X 8-Core Processor |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | B550M-ITX/ac |
| Motherboard | ASRock B550M-ITX/ac |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 7 5700X |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | AuthenticAMD Family 25 Model 33 Stepping 2 |
| Base Frequency | 3.40 GHz |
| Cluster 1 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
3352
623.4 IPS |
|
|
Image Classification (HP)
|
100% |
3333
619.8 IPS |
|
|
Image Classification (Q)
|
100% |
5369
998.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
3991
64.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
3911
63.4 IPS |
|
|
Image Segmentation (Q)
|
99% |
6286
102.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
6497
7.58 IPS |
|
|
Pose Estimation (HP)
|
100% |
6572
7.67 IPS |
|
|
Pose Estimation (Q)
|
94% |
13517
15.9 IPS |
|
|
Object Detection (SP)
|
100% |
3119
247.4 IPS |
|
|
Object Detection (HP)
|
100% |
3167
251.2 IPS |
|
|
Object Detection (Q)
|
87% |
5535
444.0 IPS |
|
|
Face Detection (SP)
|
100% |
7600
90.3 IPS |
|
|
Face Detection (HP)
|
100% |
7517
89.3 IPS |
|
|
Face Detection (Q)
|
97% |
16070
191.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
7917
61.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
7936
61.1 IPS |
|
|
Depth Estimation (Q)
|
81% |
14931
117.7 IPS |
|
|
Style Transfer (SP)
|
100% |
19202
24.7 IPS |
|
|
Style Transfer (HP)
|
100% |
18972
24.4 IPS |
|
|
Style Transfer (Q)
|
98% |
38790
50.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3929
145.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
3923
144.8 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
7869
291.5 IPS |
|
|
Text Classification (SP)
|
100% |
2935
3.92 KIPS |
|
|
Text Classification (HP)
|
100% |
3003
4.01 KIPS |
|
|
Text Classification (Q)
|
91% |
1243
1.67 KIPS |
|
|
Machine Translation (SP)
|
100% |
4834
83.3 IPS |
|
|
Machine Translation (HP)
|
100% |
4657
80.2 IPS |
|
|
Machine Translation (Q)
|
100% |
4668
80.4 IPS |
