LENOVO 81Q2
Geekbench ML Score
1544
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | February 08 2024 04:31 AM |
| Views | 17 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Insider Preview (64-bit) |
| Model | LENOVO 81Q2 |
| Motherboard | LENOVO LNVNB161216 |
| CPU Information | |
|---|---|
| Name | Intel Core i7-10510U |
| Topology | 1 Processor, 4 Cores, 8 Threads |
| Identifier | GenuineIntel Family 6 Model 142 Stepping 12 |
| Base Frequency | 2.30 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 | 36.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce MX250 |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
606
113.4 IPS |
|
|
Image Classification (F16)
|
100% |
607
113.7 IPS |
|
|
Image Classification (I8)
|
100% |
521
97.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
852
14.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
831
13.9 IPS |
|
|
Image Segmentation (I8)
|
98% |
729
12.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
6472
7.84 IPS |
|
|
Pose Estimation (F16)
|
100% |
6115
7.40 IPS |
|
|
Pose Estimation (I8)
|
100% |
5836
7.07 IPS |
|
|
Object Detection (F32)
|
100% |
625
46.6 IPS |
|
|
Object Detection (F16)
|
100% |
638
47.6 IPS |
|
|
Object Detection (I8)
|
58% |
564
42.1 IPS |
|
|
Face Detection (F32)
|
100% |
1248
14.8 IPS |
|
|
Face Detection (F16)
|
100% |
1268
15.1 IPS |
|
|
Face Detection (I8)
|
89% |
1000
11.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
2971
23.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
2905
22.5 IPS |
|
|
Depth Estimation (I8)
|
95% |
2664
20.7 IPS |
|
|
Style Transfer (F32)
|
100% |
13714
18.0 IPS |
|
|
Style Transfer (F16)
|
100% |
14419
19.0 IPS |
|
|
Style Transfer (I8)
|
98% |
11608
15.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2981
106.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
3014
107.6 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
2049
73.2 IPS |
|
|
Text Classification (F32)
|
100% |
622
893.6 IPS |
|
|
Text Classification (F16)
|
100% |
563
809.1 IPS |
|
|
Text Classification (I8)
|
98% |
418
600.2 IPS |
|
|
Machine Translation (F32)
|
100% |
905
16.7 IPS |
|
|
Machine Translation (F16)
|
100% |
910
16.7 IPS |
|
|
Machine Translation (I8)
|
68% |
481
8.85 IPS |
