Dell Inc. Precision 5570
Geekbench ML Score
6908
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 04 2025 02:46 PM |
| Views | 4 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Dell Inc. Precision 5570 |
| Motherboard | Dell Inc. 03M8N5 |
| Power Plan | High performance |
| CPU Information | |
|---|---|
| Name | Intel Core i9-12900H |
| Topology | 1 Processor, 14 Cores, 20 Threads |
| Identifier | GenuineIntel Family 6 Model 154 Stepping 3 |
| Base Frequency | 2.50 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 8 Cores |
| L1 Instruction Cache | 32.0 KB x 10 |
| L1 Data Cache | 48.0 KB x 10 |
| L2 Cache | 1.25 MB x 2 |
| L3 Cache | 24.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA RTX A2000 8GB Laptop GPU |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
3384
633.3 IPS |
|
|
Image Classification (F16)
|
100% |
3221
602.7 IPS |
|
|
Image Classification (I8)
|
100% |
2482
464.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
4213
70.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
4580
76.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
3521
58.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
32355
39.2 IPS |
|
|
Pose Estimation (F16)
|
100% |
36099
43.7 IPS |
|
|
Pose Estimation (I8)
|
100% |
28083
34.0 IPS |
|
|
Object Detection (F32)
|
100% |
3450
257.6 IPS |
|
|
Object Detection (F16)
|
100% |
3393
253.3 IPS |
|
|
Object Detection (I8)
|
61% |
2895
216.1 IPS |
|
|
Face Detection (F32)
|
100% |
8367
99.5 IPS |
|
|
Face Detection (F16)
|
100% |
8702
103.5 IPS |
|
|
Face Detection (I8)
|
89% |
6597
78.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
16993
131.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
19630
152.2 IPS |
|
|
Depth Estimation (I8)
|
94% |
14729
114.2 IPS |
|
|
Style Transfer (F32)
|
100% |
67891
89.3 IPS |
|
|
Style Transfer (F16)
|
100% |
69024
90.8 IPS |
|
|
Style Transfer (I8)
|
98% |
52663
69.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
13648
487.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
11697
417.7 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
6335
226.2 IPS |
|
|
Text Classification (F32)
|
100% |
1345
1.93 KIPS |
|
|
Text Classification (F16)
|
100% |
1586
2.28 KIPS |
|
|
Text Classification (I8)
|
98% |
741
1.07 KIPS |
|
|
Machine Translation (F32)
|
100% |
2603
47.9 IPS |
|
|
Machine Translation (F16)
|
100% |
2557
47.1 IPS |
|
|
Machine Translation (I8)
|
70% |
1199
22.1 IPS |
