LENOVO 21QESIT004
Geekbench ML Score
4826
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 27 2025 06:10 AM |
| Views | 10 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | LENOVO 21QESIT004 |
| Motherboard | LENOVO 21QESIT004 |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 7 265H |
| Topology | 1 Processor, 16 Cores |
| Identifier | GenuineIntel Family 6 Model 197 Stepping 2 |
| Base Frequency | 2.20 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 10 Cores |
| L1 Instruction Cache | 64.0 KB x 8 |
| L1 Data Cache | 48.0 KB x 8 |
| L2 Cache | 3.00 MB x 2 |
| L3 Cache | 24.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | Intel(R) Arc(TM) 140T GPU (8GB) |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
3913
732.2 IPS |
|
|
Image Classification (F16)
|
100% |
3918
733.2 IPS |
|
|
Image Classification (I8)
|
99% |
3052
571.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
3047
50.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
3128
52.2 IPS |
|
|
Image Segmentation (I8)
|
98% |
2405
40.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
19283
23.4 IPS |
|
|
Pose Estimation (F16)
|
100% |
22517
27.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
17664
21.4 IPS |
|
|
Object Detection (F32)
|
100% |
2059
153.7 IPS |
|
|
Object Detection (F16)
|
100% |
2439
182.1 IPS |
|
|
Object Detection (I8)
|
60% |
1633
121.9 IPS |
|
|
Face Detection (F32)
|
100% |
4758
56.6 IPS |
|
|
Face Detection (F16)
|
100% |
5078
60.4 IPS |
|
|
Face Detection (I8)
|
88% |
3255
38.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
12260
95.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
13947
108.2 IPS |
|
|
Depth Estimation (I8)
|
95% |
10873
84.3 IPS |
|
|
Style Transfer (F32)
|
100% |
45221
59.5 IPS |
|
|
Style Transfer (F16)
|
100% |
51843
68.2 IPS |
|
|
Style Transfer (I8)
|
98% |
32645
42.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7607
271.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
8196
292.7 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
4983
178.0 IPS |
|
|
Text Classification (F32)
|
90% |
832
1.20 KIPS |
|
|
Text Classification (F16)
|
90% |
845
1.21 KIPS |
|
|
Text Classification (I8)
|
90% |
646
928.8 IPS |
|
|
Machine Translation (F32)
|
100% |
1639
30.2 IPS |
|
|
Machine Translation (F16)
|
100% |
1718
31.6 IPS |
|
|
Machine Translation (I8)
|
70% |
1079
19.9 IPS |
