LENOVO 21QESIT004
Geekbench ML Score
5385
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 27 2025 08:30 AM |
| Views | 4 |
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 16 |
| L1 Data Cache | 32.0 KB x 16 |
| L2 Cache | 4.00 MB x 2 |
| L3 Cache | 24.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | Intel(R) Arc(TM) 140T GPU (8GB) |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
4036
755.3 IPS |
|
|
Image Classification (F16)
|
100% |
3967
742.3 IPS |
|
|
Image Classification (I8)
|
99% |
3038
568.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
3250
54.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
3265
54.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
2535
42.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
23911
29.0 IPS |
|
|
Pose Estimation (F16)
|
100% |
23489
28.4 IPS |
|
|
Pose Estimation (I8)
|
100% |
18468
22.4 IPS |
|
|
Object Detection (F32)
|
100% |
2975
222.1 IPS |
|
|
Object Detection (F16)
|
100% |
3178
237.3 IPS |
|
|
Object Detection (I8)
|
60% |
2458
183.5 IPS |
|
|
Face Detection (F32)
|
100% |
5605
66.7 IPS |
|
|
Face Detection (F16)
|
100% |
5594
66.5 IPS |
|
|
Face Detection (I8)
|
88% |
3808
45.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
14540
112.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
14046
108.9 IPS |
|
|
Depth Estimation (I8)
|
95% |
11504
89.2 IPS |
|
|
Style Transfer (F32)
|
100% |
54227
71.3 IPS |
|
|
Style Transfer (F16)
|
100% |
53765
70.7 IPS |
|
|
Style Transfer (I8)
|
98% |
38205
50.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
9007
321.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
8536
304.8 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
5474
195.5 IPS |
|
|
Text Classification (F32)
|
90% |
838
1.20 KIPS |
|
|
Text Classification (F16)
|
90% |
878
1.26 KIPS |
|
|
Text Classification (I8)
|
90% |
623
895.9 IPS |
|
|
Machine Translation (F32)
|
100% |
2055
37.8 IPS |
|
|
Machine Translation (F16)
|
100% |
1987
36.6 IPS |
|
|
Machine Translation (I8)
|
70% |
1112
20.5 IPS |
