SAMSUNG ELECTRONICS CO., LTD. 940XHA
Geekbench ML Score
5642
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | April 24 2025 02:07 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | SAMSUNG ELECTRONICS CO., LTD. 940XHA |
| Motherboard | SAMSUNG ELECTRONICS CO., LTD. NP940XHA-KG1UK |
| Power Plan | SAMSUNG MODE |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 7 256V |
| Topology | 1 Processor, 8 Cores |
| Identifier | GenuineIntel Family 6 Model 189 Stepping 1 |
| Base Frequency | 2.20 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 4 Cores |
| L1 Instruction Cache | 64.0 KB x 4 |
| L1 Data Cache | 48.0 KB x 4 |
| L2 Cache | 2.50 MB x 1 |
| L3 Cache | 12.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | Intel(R) Arc(TM) 140V GPU (8GB) |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
2633
492.7 IPS |
|
|
Image Classification (F16)
|
100% |
2753
515.2 IPS |
|
|
Image Classification (I8)
|
100% |
2340
438.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
6089
101.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
6086
101.6 IPS |
|
|
Image Segmentation (I8)
|
98% |
4570
76.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
19780
24.0 IPS |
|
|
Pose Estimation (F16)
|
100% |
20214
24.5 IPS |
|
|
Pose Estimation (I8)
|
100% |
16882
20.4 IPS |
|
|
Object Detection (F32)
|
100% |
2824
210.8 IPS |
|
|
Object Detection (F16)
|
100% |
2909
217.2 IPS |
|
|
Object Detection (I8)
|
61% |
2437
181.9 IPS |
|
|
Face Detection (F32)
|
100% |
7627
90.7 IPS |
|
|
Face Detection (F16)
|
100% |
8157
97.0 IPS |
|
|
Face Detection (I8)
|
89% |
5178
61.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
18142
140.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
17724
137.5 IPS |
|
|
Depth Estimation (I8)
|
94% |
15332
118.9 IPS |
|
|
Style Transfer (F32)
|
100% |
46191
60.8 IPS |
|
|
Style Transfer (F16)
|
100% |
47121
62.0 IPS |
|
|
Style Transfer (I8)
|
98% |
39116
51.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7902
282.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
8200
292.8 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
4875
174.1 IPS |
|
|
Text Classification (F32)
|
100% |
630
905.4 IPS |
|
|
Text Classification (F16)
|
100% |
661
950.4 IPS |
|
|
Text Classification (I8)
|
98% |
565
811.8 IPS |
|
|
Machine Translation (F32)
|
100% |
2603
47.9 IPS |
|
|
Machine Translation (F16)
|
100% |
2633
48.5 IPS |
|
|
Machine Translation (I8)
|
70% |
1311
24.1 IPS |
