Wizard-2025 5090 Micro-Star International Co., Ltd. MS-7E59
Geekbench AI Score
50430
Single Precision Score
77038
Half Precision Score
36734
Quantized Score
Geekbench AI 1.6.0 for Windows AVX2
Result Information
| User | joslloyd |
| Upload Date | January 01 2026 07:57 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 5090 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Micro-Star International Co., Ltd. MS-7E59 |
| Motherboard | Micro-Star International Co., Ltd. MAG X870E TOMAHAWK WIFI (MS-7E59) |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 9 9900X |
| Topology | 1 Processor, 12 Cores, 24 Threads |
| Identifier | AuthenticAMD Family 26 Model 68 Stepping 0 |
| Base Frequency | 4.40 GHz |
| Cluster 1 | 12 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
17976
3.34 KIPS |
|
|
Image Classification (HP)
|
100% |
23571
4.38 KIPS |
|
|
Image Classification (Q)
|
100% |
15338
2.85 KIPS |
|
|
Image Segmentation (SP)
|
100% |
39832
645.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
52052
843.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
36759
597.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
411076
479.7 IPS |
|
|
Pose Estimation (HP)
|
100% |
1028404
1.20 KIPS |
|
|
Pose Estimation (Q)
|
96% |
329374
385.8 IPS |
|
|
Object Detection (SP)
|
100% |
26557
2.11 KIPS |
|
|
Object Detection (HP)
|
100% |
35391
2.81 KIPS |
|
|
Object Detection (Q)
|
85% |
21370
1.72 KIPS |
|
|
Face Detection (SP)
|
100% |
78849
936.9 IPS |
|
|
Face Detection (HP)
|
100% |
108083
1.28 KIPS |
|
|
Face Detection (Q)
|
97% |
62036
739.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
108645
837.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
196820
1.52 KIPS |
|
|
Depth Estimation (Q)
|
77% |
78461
628.4 IPS |
|
|
Style Transfer (SP)
|
100% |
621340
798.7 IPS |
|
|
Style Transfer (HP)
|
100% |
1859400
2.39 KIPS |
|
|
Style Transfer (Q)
|
98% |
517087
666.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
78596
2.90 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
104012
3.84 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
55178
2.04 KIPS |
|
|
Text Classification (SP)
|
100% |
4166
5.56 KIPS |
|
|
Text Classification (HP)
|
100% |
5128
6.84 KIPS |
|
|
Text Classification (Q)
|
97% |
2463
3.30 KIPS |
|
|
Machine Translation (SP)
|
100% |
7810
134.5 IPS |
|
|
Machine Translation (HP)
|
100% |
7816
134.6 IPS |
|
|
Machine Translation (Q)
|
70% |
3296
61.8 IPS |
