Gigabyte Technology Co., Ltd. X870E AORUS MASTER
Geekbench AI Score
14835
Single Precision Score
14525
Half Precision Score
32299
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| Upload Date | June 29 2025 06:23 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | CPU |
| Device | AMD Ryzen 9 9950X3D 16-Core Processor |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Gigabyte Technology Co., Ltd. X870E AORUS MASTER |
| Motherboard | Gigabyte Technology Co., Ltd. X870E AORUS MASTER |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 9 9950X3D |
| Topology | 1 Processor, 16 Cores, 32 Threads |
| Identifier | AuthenticAMD Family 26 Model 68 Stepping 0 |
| Base Frequency | 4.30 GHz |
| Cluster 1 | 16 Cores |
| Memory Information | |
|---|---|
| Size | 128.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
6956
1.29 KIPS |
|
|
Image Classification (HP)
|
100% |
7043
1.31 KIPS |
|
|
Image Classification (Q)
|
100% |
15682
2.92 KIPS |
|
|
Image Segmentation (SP)
|
100% |
10039
162.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
9128
148.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
22243
360.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
32817
38.3 IPS |
|
|
Pose Estimation (HP)
|
100% |
32911
38.4 IPS |
|
|
Pose Estimation (Q)
|
98% |
129147
151.2 IPS |
|
|
Object Detection (SP)
|
100% |
8546
677.8 IPS |
|
|
Object Detection (HP)
|
100% |
8471
671.9 IPS |
|
|
Object Detection (Q)
|
88% |
18011
1.44 KIPS |
|
|
Face Detection (SP)
|
100% |
19864
236.0 IPS |
|
|
Face Detection (HP)
|
100% |
17969
213.5 IPS |
|
|
Face Detection (Q)
|
100% |
48534
576.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
25908
199.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
27720
213.6 IPS |
|
|
Depth Estimation (Q)
|
88% |
63115
491.1 IPS |
|
|
Style Transfer (SP)
|
100% |
83404
107.2 IPS |
|
|
Style Transfer (HP)
|
100% |
83095
106.8 IPS |
|
|
Style Transfer (Q)
|
98% |
297122
383.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
15607
576.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
15463
571.0 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
39398
1.46 KIPS |
|
|
Text Classification (SP)
|
100% |
5345
7.13 KIPS |
|
|
Text Classification (HP)
|
100% |
5050
6.74 KIPS |
|
|
Text Classification (Q)
|
92% |
6011
8.07 KIPS |
|
|
Machine Translation (SP)
|
100% |
7366
126.9 IPS |
|
|
Machine Translation (HP)
|
100% |
7220
124.4 IPS |
|
|
Machine Translation (Q)
|
100% |
7066
121.7 IPS |
