Micro-Star International Co., Ltd. MS-7E26
Geekbench AI Score
34400
Single Precision Score
46567
Half Precision Score
29276
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| Upload Date | September 23 2025 09:34 AM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | AMD Radeon RX 9070 XT |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Micro-Star International Co., Ltd. MS-7E26 |
| Motherboard | Micro-Star International Co., Ltd. B650 GAMING PLUS WIFI (MS-7E26) |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 5 9600X |
| Topology | 1 Processor, 6 Cores, 12 Threads |
| Identifier | AuthenticAMD Family 26 Model 68 Stepping 0 |
| Base Frequency | 3.90 GHz |
| Cluster 1 | 6 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
16531
3.07 KIPS |
|
|
Image Classification (HP)
|
100% |
18531
3.45 KIPS |
|
|
Image Classification (Q)
|
99% |
15306
2.85 KIPS |
|
|
Image Segmentation (SP)
|
100% |
16604
269.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
18912
306.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
20944
340.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
212383
247.8 IPS |
|
|
Pose Estimation (HP)
|
100% |
614585
717.1 IPS |
|
|
Pose Estimation (Q)
|
96% |
192372
225.3 IPS |
|
|
Object Detection (SP)
|
100% |
17379
1.38 KIPS |
|
|
Object Detection (HP)
|
99% |
20639
1.64 KIPS |
|
|
Object Detection (Q)
|
87% |
16091
1.29 KIPS |
|
|
Face Detection (SP)
|
100% |
48516
576.5 IPS |
|
|
Face Detection (HP)
|
100% |
53112
631.1 IPS |
|
|
Face Detection (Q)
|
97% |
42812
510.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
87002
670.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
128925
993.3 IPS |
|
|
Depth Estimation (Q)
|
77% |
72276
579.2 IPS |
|
|
Style Transfer (SP)
|
100% |
384389
494.1 IPS |
|
|
Style Transfer (HP)
|
100% |
712773
916.3 IPS |
|
|
Style Transfer (Q)
|
98% |
350966
452.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
53153
1.96 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
86529
3.20 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
44196
1.64 KIPS |
|
|
Text Classification (SP)
|
100% |
4792
6.40 KIPS |
|
|
Text Classification (HP)
|
100% |
4533
6.05 KIPS |
|
|
Text Classification (Q)
|
97% |
2826
3.79 KIPS |
|
|
Machine Translation (SP)
|
100% |
5544
95.5 IPS |
|
|
Machine Translation (HP)
|
100% |
5635
97.1 IPS |
|
|
Machine Translation (Q)
|
70% |
3437
64.5 IPS |
