Dell Inc. XPS 15 7590
Geekbench ML Score
1303
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | June 23 2025 09:00 AM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 10 Pro (64-bit) |
| Model | Dell Inc. XPS 15 7590 |
| Motherboard | Dell Inc. 095Y8K |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i5-9300H |
| Topology | 1 Processor, 4 Cores, 8 Threads |
| Identifier | GenuineIntel Family 6 Model 158 Stepping 10 |
| Base Frequency | 2.40 GHz |
| Cluster 1 | 4 Cores |
| L1 Instruction Cache | 32.0 KB x 4 |
| L1 Data Cache | 32.0 KB x 4 |
| L2 Cache | 256 KB x 4 |
| L3 Cache | 8.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 8.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
708
132.5 IPS |
|
|
Image Classification (F16)
|
100% |
688
128.7 IPS |
|
|
Image Classification (I8)
|
97% |
1185
221.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
546
9.13 IPS |
|
|
Image Segmentation (F16)
|
100% |
556
9.28 IPS |
|
|
Image Segmentation (I8)
|
97% |
880
14.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
1874
2.27 IPS |
|
|
Pose Estimation (F16)
|
100% |
1938
2.35 IPS |
|
|
Pose Estimation (I8)
|
100% |
3871
4.69 IPS |
|
|
Object Detection (F32)
|
100% |
639
47.7 IPS |
|
|
Object Detection (F16)
|
100% |
821
61.3 IPS |
|
|
Object Detection (I8)
|
60% |
728
54.3 IPS |
|
|
Face Detection (F32)
|
100% |
1144
13.6 IPS |
|
|
Face Detection (F16)
|
100% |
1132
13.5 IPS |
|
|
Face Detection (I8)
|
87% |
1994
23.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
2242
17.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
2262
17.5 IPS |
|
|
Depth Estimation (I8)
|
74% |
3891
30.2 IPS |
|
|
Style Transfer (F32)
|
100% |
5294
6.96 IPS |
|
|
Style Transfer (F16)
|
100% |
5117
6.73 IPS |
|
|
Style Transfer (I8)
|
85% |
6687
8.80 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
905
32.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
966
34.5 IPS |
|
|
Image Super-Resolution (I8)
|
97% |
1511
54.0 IPS |
|
|
Text Classification (F32)
|
100% |
907
1.30 KIPS |
|
|
Text Classification (F16)
|
100% |
938
1.35 KIPS |
|
|
Text Classification (I8)
|
94% |
279
400.5 IPS |
|
|
Machine Translation (F32)
|
100% |
1008
18.5 IPS |
|
|
Machine Translation (F16)
|
100% |
999
18.4 IPS |
|
|
Machine Translation (I8)
|
67% |
1187
21.9 IPS |
