SAMSUNG ELECTRONICS CO., LTD. 750XDA
Geekbench ML Score
1940
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 23 2025 04:02 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | SAMSUNG ELECTRONICS CO., LTD. 750XDA |
| Motherboard | SAMSUNG ELECTRONICS CO., LTD. NP750XDA-KDDIT |
| Power Plan | Samsung Mode |
| CPU Information | |
|---|---|
| Name | Intel Core i5-1135G7 |
| Topology | 1 Processor, 4 Cores, 8 Threads |
| Identifier | GenuineIntel Family 6 Model 140 Stepping 1 |
| Base Frequency | 2.42 GHz |
| Cluster 1 | 4 Cores |
| L1 Instruction Cache | 32.0 KB x 4 |
| L1 Data Cache | 48.0 KB x 4 |
| L2 Cache | 1.25 MB x 4 |
| L3 Cache | 8.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 8.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | Intel(R) Iris(R) Xe Graphics |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
950
177.8 IPS |
|
|
Image Classification (F16)
|
100% |
952
178.1 IPS |
|
|
Image Classification (I8)
|
100% |
764
143.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
1363
22.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
1353
22.6 IPS |
|
|
Image Segmentation (I8)
|
98% |
1018
17.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
8814
10.7 IPS |
|
|
Pose Estimation (F16)
|
100% |
9045
11.0 IPS |
|
|
Pose Estimation (I8)
|
100% |
4821
5.84 IPS |
|
|
Object Detection (F32)
|
100% |
1022
76.3 IPS |
|
|
Object Detection (F16)
|
100% |
1026
76.6 IPS |
|
|
Object Detection (I8)
|
54% |
841
62.8 IPS |
|
|
Face Detection (F32)
|
100% |
2149
25.5 IPS |
|
|
Face Detection (F16)
|
100% |
2107
25.1 IPS |
|
|
Face Detection (I8)
|
89% |
1454
17.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
4882
37.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
4879
37.8 IPS |
|
|
Depth Estimation (I8)
|
95% |
3497
27.1 IPS |
|
|
Style Transfer (F32)
|
100% |
19862
26.1 IPS |
|
|
Style Transfer (F16)
|
100% |
19846
26.1 IPS |
|
|
Style Transfer (I8)
|
98% |
12783
16.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3077
109.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
3072
109.7 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
1341
47.9 IPS |
|
|
Text Classification (F32)
|
100% |
555
797.6 IPS |
|
|
Text Classification (F16)
|
100% |
538
772.6 IPS |
|
|
Text Classification (I8)
|
98% |
333
479.1 IPS |
|
|
Machine Translation (F32)
|
100% |
811
14.9 IPS |
|
|
Machine Translation (F16)
|
100% |
810
14.9 IPS |
|
|
Machine Translation (I8)
|
70% |
429
7.89 IPS |
