Micro-Star International Co., Ltd. MS-7D99
Geekbench AI Score
9502
Single Precision Score
18270
Half Precision Score
6456
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| Upload Date | October 07 2025 02:57 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 3050 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Micro-Star International Co., Ltd. MS-7D99 |
| Motherboard | Micro-Star International Co., Ltd. PRO B760M-A WIFI (MS-7D99) |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i5-14600K |
| Topology | 1 Processor, 14 Cores, 20 Threads |
| Identifier | GenuineIntel Family 6 Model 183 Stepping 1 |
| Base Frequency | 3.50 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
4236
787.8 IPS |
|
|
Image Classification (HP)
|
99% |
8573
1.60 KIPS |
|
|
Image Classification (Q)
|
99% |
3347
624.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
5826
94.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
9721
157.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
4733
77.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
37031
43.2 IPS |
|
|
Pose Estimation (HP)
|
100% |
126449
147.5 IPS |
|
|
Pose Estimation (Q)
|
96% |
31988
37.5 IPS |
|
|
Object Detection (SP)
|
100% |
4741
376.1 IPS |
|
|
Object Detection (HP)
|
100% |
9991
792.5 IPS |
|
|
Object Detection (Q)
|
84% |
3711
299.3 IPS |
|
|
Face Detection (SP)
|
100% |
9075
107.8 IPS |
|
|
Face Detection (HP)
|
100% |
17040
202.5 IPS |
|
|
Face Detection (Q)
|
97% |
7122
84.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
21583
166.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
47793
368.2 IPS |
|
|
Depth Estimation (Q)
|
77% |
15849
127.0 IPS |
|
|
Style Transfer (SP)
|
100% |
66500
85.5 IPS |
|
|
Style Transfer (HP)
|
100% |
183860
236.4 IPS |
|
|
Style Transfer (Q)
|
98% |
52086
67.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
14110
521.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
26967
995.8 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
8275
306.4 IPS |
|
|
Text Classification (SP)
|
100% |
2579
3.44 KIPS |
|
|
Text Classification (HP)
|
99% |
3194
4.26 KIPS |
|
|
Text Classification (Q)
|
97% |
1256
1.68 KIPS |
|
|
Machine Translation (SP)
|
100% |
2924
50.4 IPS |
|
|
Machine Translation (HP)
|
100% |
3053
52.6 IPS |
|
|
Machine Translation (Q)
|
70% |
1096
20.6 IPS |
