PowerSpec - G478 Micro-Star International Co., Ltd. MS-7D91
Geekbench ML Score
26647
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| User | BlackMagic |
| Upload Date | May 23 2025 01:30 AM |
| Views | 5 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Micro-Star International Co., Ltd. MS-7D91 |
| Motherboard | Micro-Star International Co., Ltd. MPG Z790 EDGE WIFI (MS-7D91) |
| Power Plan | Ultimate Performance |
| CPU Information | |
|---|---|
| Name | Intel Core i9-14900KF |
| Topology | 1 Processor, 24 Cores, 32 Threads |
| Identifier | GenuineIntel Family 6 Model 183 Stepping 1 |
| Base Frequency | 3.20 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 16 Cores |
| L1 Instruction Cache | 32.0 KB x 16 |
| L1 Data Cache | 48.0 KB x 16 |
| L2 Cache | 2.00 MB x 4 |
| L3 Cache | 36.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 128.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 4080 SUPER |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
11836
2.21 KIPS |
|
|
Image Classification (F16)
|
100% |
12291
2.30 KIPS |
|
|
Image Classification (I8)
|
100% |
10626
1.99 KIPS |
|
|
Image Segmentation (F32)
|
100% |
17406
290.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
17903
299.0 IPS |
|
|
Image Segmentation (I8)
|
98% |
16001
267.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
243023
294.3 IPS |
|
|
Pose Estimation (F16)
|
100% |
243023
294.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
214737
260.0 IPS |
|
|
Object Detection (F32)
|
100% |
8665
646.9 IPS |
|
|
Object Detection (F16)
|
100% |
8507
635.1 IPS |
|
|
Object Detection (I8)
|
56% |
7824
584.1 IPS |
|
|
Face Detection (F32)
|
100% |
39564
470.4 IPS |
|
|
Face Detection (F16)
|
100% |
40842
485.6 IPS |
|
|
Face Detection (I8)
|
89% |
33581
399.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
82348
638.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
77042
597.5 IPS |
|
|
Depth Estimation (I8)
|
94% |
60804
471.5 IPS |
|
|
Style Transfer (F32)
|
100% |
356057
468.4 IPS |
|
|
Style Transfer (F16)
|
100% |
356196
468.5 IPS |
|
|
Style Transfer (I8)
|
98% |
314990
414.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
50002
1.79 KIPS |
|
|
Image Super-Resolution (F16)
|
100% |
48775
1.74 KIPS |
|
|
Image Super-Resolution (I8)
|
99% |
37111
1.33 KIPS |
|
|
Text Classification (F32)
|
100% |
3254
4.68 KIPS |
|
|
Text Classification (F16)
|
100% |
3271
4.70 KIPS |
|
|
Text Classification (I8)
|
98% |
2035
2.92 KIPS |
|
|
Machine Translation (F32)
|
100% |
4775
87.9 IPS |
|
|
Machine Translation (F16)
|
100% |
4797
88.3 IPS |
|
|
Machine Translation (I8)
|
70% |
2781
51.2 IPS |
