SAMSUNG ELECTRONICS CO., LTD. 960XGL
Geekbench ML Score
12868
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | September 23 2024 03:06 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. NP960XGL-XG1UK |
| 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% |
5908
1.11 KIPS |
|
|
Image Classification (F16)
|
100% |
6651
1.24 KIPS |
|
|
Image Classification (I8)
|
100% |
5969
1.12 KIPS |
|
|
Image Segmentation (F32)
|
100% |
8978
149.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
9092
151.9 IPS |
|
|
Image Segmentation (I8)
|
98% |
8252
137.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
80492
97.5 IPS |
|
|
Pose Estimation (F16)
|
100% |
80704
97.7 IPS |
|
|
Pose Estimation (I8)
|
100% |
70701
85.6 IPS |
|
|
Object Detection (F32)
|
100% |
4350
324.7 IPS |
|
|
Object Detection (F16)
|
100% |
4118
307.5 IPS |
|
|
Object Detection (I8)
|
63% |
4180
312.1 IPS |
|
|
Face Detection (F32)
|
100% |
18453
219.4 IPS |
|
|
Face Detection (F16)
|
100% |
18554
220.6 IPS |
|
|
Face Detection (I8)
|
89% |
15612
185.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
39320
304.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
29744
230.7 IPS |
|
|
Depth Estimation (I8)
|
94% |
32525
252.2 IPS |
|
|
Style Transfer (F32)
|
100% |
156689
206.1 IPS |
|
|
Style Transfer (F16)
|
100% |
116059
152.7 IPS |
|
|
Style Transfer (I8)
|
98% |
102822
135.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
24195
864.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
23991
856.8 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
17576
627.7 IPS |
|
|
Text Classification (F32)
|
100% |
1965
2.82 KIPS |
|
|
Text Classification (F16)
|
100% |
1967
2.83 KIPS |
|
|
Text Classification (I8)
|
98% |
1262
1.81 KIPS |
|
|
Machine Translation (F32)
|
100% |
3199
58.9 IPS |
|
|
Machine Translation (F16)
|
100% |
3200
58.9 IPS |
|
|
Machine Translation (I8)
|
70% |
1837
33.8 IPS |
