SAMSUNG ELECTRONICS CO., LTD. 960XHA
Geekbench ML Score
5658
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | January 25 2025 06:24 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | SAMSUNG ELECTRONICS CO., LTD. 960XHA |
| Motherboard | SAMSUNG ELECTRONICS CO., LTD. NP960XHA-KG2US |
| 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% |
2566
480.2 IPS |
|
|
Image Classification (F16)
|
100% |
2766
517.5 IPS |
|
|
Image Classification (I8)
|
100% |
2294
429.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
6072
101.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
6015
100.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
4583
76.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
21357
25.9 IPS |
|
|
Pose Estimation (F16)
|
100% |
21203
25.7 IPS |
|
|
Pose Estimation (I8)
|
100% |
18281
22.1 IPS |
|
|
Object Detection (F32)
|
100% |
2938
219.3 IPS |
|
|
Object Detection (F16)
|
100% |
3411
254.6 IPS |
|
|
Object Detection (I8)
|
61% |
2553
190.6 IPS |
|
|
Face Detection (F32)
|
100% |
7957
94.6 IPS |
|
|
Face Detection (F16)
|
100% |
7789
92.6 IPS |
|
|
Face Detection (I8)
|
89% |
5139
61.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
18414
142.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
17499
135.7 IPS |
|
|
Depth Estimation (I8)
|
94% |
15495
120.2 IPS |
|
|
Style Transfer (F32)
|
100% |
45962
60.5 IPS |
|
|
Style Transfer (F16)
|
100% |
44039
57.9 IPS |
|
|
Style Transfer (I8)
|
98% |
34788
45.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7379
263.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
7506
268.1 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
4716
168.4 IPS |
|
|
Text Classification (F32)
|
100% |
589
846.3 IPS |
|
|
Text Classification (F16)
|
100% |
695
998.9 IPS |
|
|
Text Classification (I8)
|
98% |
579
832.7 IPS |
|
|
Machine Translation (F32)
|
100% |
2585
47.6 IPS |
|
|
Machine Translation (F16)
|
100% |
2790
51.3 IPS |
|
|
Machine Translation (I8)
|
70% |
1318
24.3 IPS |
