SAMSUNG ELECTRONICS CO., LTD. 960XGL
Geekbench ML Score
12533
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | August 16 2024 03:12 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | SAMSUNG ELECTRONICS CO., LTD. 960XGL |
| Motherboard | SAMSUNG ELECTRONICS CO., LTD. NT960XGL-X92AG |
| Power Plan | SAMSUNG MODE |
| CPU Information | |
|---|---|
| Name | Intel Core Ultra 9 185H |
| Topology | 1 Processor, 16 Cores, 22 Threads |
| Identifier | GenuineIntel Family 6 Model 170 Stepping 4 |
| Base Frequency | 2.50 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 10 Cores |
| L1 Instruction Cache | 64.0 KB x 11 |
| L1 Data Cache | 48.0 KB x 11 |
| L2 Cache | 2.00 MB x 2 |
| L3 Cache | 24.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 4070 Laptop GPU |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
6654
1.25 KIPS |
|
|
Image Classification (F16)
|
100% |
6710
1.26 KIPS |
|
|
Image Classification (I8)
|
100% |
6028
1.13 KIPS |
|
|
Image Segmentation (F32)
|
100% |
8900
148.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
8986
150.1 IPS |
|
|
Image Segmentation (I8)
|
98% |
8086
135.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
74020
89.6 IPS |
|
|
Pose Estimation (F16)
|
100% |
76449
92.6 IPS |
|
|
Pose Estimation (I8)
|
100% |
75728
91.7 IPS |
|
|
Object Detection (F32)
|
100% |
4431
330.8 IPS |
|
|
Object Detection (F16)
|
100% |
4562
340.6 IPS |
|
|
Object Detection (I8)
|
63% |
4126
308.0 IPS |
|
|
Face Detection (F32)
|
100% |
17668
210.1 IPS |
|
|
Face Detection (F16)
|
100% |
17842
212.1 IPS |
|
|
Face Detection (I8)
|
89% |
15623
185.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
30518
236.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
39989
310.1 IPS |
|
|
Depth Estimation (I8)
|
95% |
23858
185.0 IPS |
|
|
Style Transfer (F32)
|
100% |
152237
200.3 IPS |
|
|
Style Transfer (F16)
|
100% |
113532
149.3 IPS |
|
|
Style Transfer (I8)
|
98% |
103487
136.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
21944
783.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
21833
779.7 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
15811
564.7 IPS |
|
|
Text Classification (F32)
|
100% |
1715
2.46 KIPS |
|
|
Text Classification (F16)
|
100% |
1977
2.84 KIPS |
|
|
Text Classification (I8)
|
98% |
1160
1.67 KIPS |
|
|
Machine Translation (F32)
|
100% |
3138
57.7 IPS |
|
|
Machine Translation (F16)
|
100% |
3165
58.3 IPS |
|
|
Machine Translation (I8)
|
70% |
1852
34.1 IPS |
