SAMSUNG ELECTRONICS CO., LTD. 960QHA
Geekbench ML Score
3486
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | October 10 2024 09:05 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | SAMSUNG ELECTRONICS CO., LTD. 960QHA |
| Motherboard | SAMSUNG ELECTRONICS CO., LTD. NP960QHA-MSO |
| Power Plan | SAMSUNG MODE |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 7 258V |
| 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 | 32.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1541
288.3 IPS |
|
|
Image Classification (F16)
|
100% |
1808
338.4 IPS |
|
|
Image Classification (I8)
|
99% |
3238
606.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
1563
26.1 IPS |
|
|
Image Segmentation (F16)
|
100% |
1616
27.0 IPS |
|
|
Image Segmentation (I8)
|
98% |
2623
43.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
5187
6.28 IPS |
|
|
Pose Estimation (F16)
|
100% |
5077
6.15 IPS |
|
|
Pose Estimation (I8)
|
100% |
17964
21.8 IPS |
|
|
Object Detection (F32)
|
100% |
1823
136.1 IPS |
|
|
Object Detection (F16)
|
100% |
1824
136.2 IPS |
|
|
Object Detection (I8)
|
62% |
1776
132.6 IPS |
|
|
Face Detection (F32)
|
100% |
4082
48.5 IPS |
|
|
Face Detection (F16)
|
100% |
4144
49.3 IPS |
|
|
Face Detection (I8)
|
89% |
4384
52.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
6386
49.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
6364
49.4 IPS |
|
|
Depth Estimation (I8)
|
96% |
13064
101.3 IPS |
|
|
Style Transfer (F32)
|
100% |
12570
16.5 IPS |
|
|
Style Transfer (F16)
|
100% |
12744
16.8 IPS |
|
|
Style Transfer (I8)
|
98% |
21692
28.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2707
96.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2765
98.7 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
4632
165.4 IPS |
|
|
Text Classification (F32)
|
100% |
1317
1.89 KIPS |
|
|
Text Classification (F16)
|
100% |
1336
1.92 KIPS |
|
|
Text Classification (I8)
|
98% |
1183
1.70 KIPS |
|
|
Machine Translation (F32)
|
100% |
1992
36.7 IPS |
|
|
Machine Translation (F16)
|
100% |
2086
38.4 IPS |
|
|
Machine Translation (I8)
|
67% |
2724
50.1 IPS |
