Micro-Star International Co., Ltd. MS-7C71
Geekbench ML Score
15140
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| User | Paul_Kim |
| Upload Date | January 30 2025 01:45 AM |
| Views | 4 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Micro-Star International Co., Ltd. MS-7C71 |
| Motherboard | Micro-Star International Co., Ltd. MEG Z490 UNIFY (MS-7C71) |
| CPU Information | |
|---|---|
| Name | Intel Core i9-10900K |
| Topology | 1 Processor, 10 Cores, 20 Threads |
| Identifier | GenuineIntel Family 6 Model 165 Stepping 5 |
| Base Frequency | 3.70 GHz |
| Cluster 1 | 10 Cores |
| L1 Instruction Cache | 32.0 KB x 10 |
| L1 Data Cache | 32.0 KB x 10 |
| L2 Cache | 256 KB x 10 |
| L3 Cache | 20.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 3080 |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
7272
1.36 KIPS |
|
|
Image Classification (F16)
|
100% |
7536
1.41 KIPS |
|
|
Image Classification (I8)
|
100% |
5060
946.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
10710
178.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
11181
186.7 IPS |
|
|
Image Segmentation (I8)
|
98% |
8334
139.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
128658
155.8 IPS |
|
|
Pose Estimation (F16)
|
100% |
127380
154.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
99414
120.4 IPS |
|
|
Object Detection (F32)
|
100% |
4117
307.3 IPS |
|
|
Object Detection (F16)
|
100% |
4084
304.9 IPS |
|
|
Object Detection (I8)
|
56% |
3569
266.4 IPS |
|
|
Face Detection (F32)
|
100% |
23193
275.8 IPS |
|
|
Face Detection (F16)
|
100% |
23663
281.4 IPS |
|
|
Face Detection (I8)
|
89% |
15730
187.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
51259
397.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
50628
392.6 IPS |
|
|
Depth Estimation (I8)
|
94% |
32375
251.1 IPS |
|
|
Style Transfer (F32)
|
100% |
228405
300.4 IPS |
|
|
Style Transfer (F16)
|
100% |
228133
300.1 IPS |
|
|
Style Transfer (I8)
|
98% |
166398
218.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
30428
1.09 KIPS |
|
|
Image Super-Resolution (F16)
|
100% |
31175
1.11 KIPS |
|
|
Image Super-Resolution (I8)
|
99% |
18136
647.7 IPS |
|
|
Text Classification (F32)
|
100% |
2564
3.68 KIPS |
|
|
Text Classification (F16)
|
100% |
2503
3.60 KIPS |
|
|
Text Classification (I8)
|
98% |
1287
1.85 KIPS |
|
|
Machine Translation (F32)
|
100% |
2772
51.0 IPS |
|
|
Machine Translation (F16)
|
100% |
2732
50.3 IPS |
|
|
Machine Translation (I8)
|
70% |
1386
25.5 IPS |
