SAMSUNG ELECTRONICS CO., LTD. 960QFG
Geekbench ML Score
7842
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | October 23 2024 04:03 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | SAMSUNG ELECTRONICS CO., LTD. 960QFG |
| Motherboard | SAMSUNG ELECTRONICS CO., LTD. NP960QFG-KB1US |
| Power Plan | SAMSUNG MODE |
| CPU Information | |
|---|---|
| Name | Intel Core i7-1360P |
| Topology | 1 Processor, 12 Cores, 16 Threads |
| Identifier | GenuineIntel Family 6 Model 186 Stepping 2 |
| Base Frequency | 2.20 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 8 Cores |
| L1 Instruction Cache | 32.0 KB x 8 |
| L1 Data Cache | 48.0 KB x 8 |
| L2 Cache | 1.25 MB x 2 |
| L3 Cache | 18.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 2070 |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
3351
627.0 IPS |
|
|
Image Classification (F16)
|
100% |
3340
625.1 IPS |
|
|
Image Classification (I8)
|
100% |
2896
541.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
4837
80.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
4896
81.8 IPS |
|
|
Image Segmentation (I8)
|
98% |
4150
69.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
49414
59.8 IPS |
|
|
Pose Estimation (F16)
|
100% |
60463
73.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
53281
64.5 IPS |
|
|
Object Detection (F32)
|
100% |
3623
270.5 IPS |
|
|
Object Detection (F16)
|
100% |
3038
226.8 IPS |
|
|
Object Detection (I8)
|
61% |
2527
188.6 IPS |
|
|
Face Detection (F32)
|
100% |
10389
123.5 IPS |
|
|
Face Detection (F16)
|
100% |
10333
122.9 IPS |
|
|
Face Detection (I8)
|
89% |
8590
102.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
28548
221.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
27265
211.4 IPS |
|
|
Depth Estimation (I8)
|
95% |
20736
160.8 IPS |
|
|
Style Transfer (F32)
|
100% |
100291
131.9 IPS |
|
|
Style Transfer (F16)
|
100% |
79382
104.4 IPS |
|
|
Style Transfer (I8)
|
98% |
67327
88.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
14719
525.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
14797
528.5 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
9875
352.7 IPS |
|
|
Text Classification (F32)
|
100% |
1093
1.57 KIPS |
|
|
Text Classification (F16)
|
100% |
1112
1.60 KIPS |
|
|
Text Classification (I8)
|
98% |
928
1.33 KIPS |
|
|
Machine Translation (F32)
|
100% |
1603
29.5 IPS |
|
|
Machine Translation (F16)
|
100% |
1581
29.1 IPS |
|
|
Machine Translation (I8)
|
70% |
986
18.1 IPS |
