LENOVO 30H0006AGE
Geekbench ML Score
5174
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | September 12 2024 11:03 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | LENOVO 30H0006AGE |
| Motherboard | LENOVO 3333 |
| Power Plan | Lenovo Default |
| CPU Information | |
|---|---|
| Name | Intel Core i9-14900 |
| Topology | 1 Processor, 24 Cores, 32 Threads |
| Identifier | GenuineIntel Family 6 Model 183 Stepping 1 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 16 Cores |
| L1 Instruction Cache | 32.0 KB x 16 |
| L1 Data Cache | 48.0 KB x 16 |
| L2 Cache | 2.00 MB x 4 |
| L3 Cache | 36.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA T1000 8GB |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
2411
451.1 IPS |
|
|
Image Classification (F16)
|
100% |
2425
453.9 IPS |
|
|
Image Classification (I8)
|
100% |
1966
368.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
3637
60.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
3297
55.1 IPS |
|
|
Image Segmentation (I8)
|
98% |
3133
52.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
22015
26.7 IPS |
|
|
Pose Estimation (F16)
|
100% |
21184
25.7 IPS |
|
|
Pose Estimation (I8)
|
100% |
18982
23.0 IPS |
|
|
Object Detection (F32)
|
100% |
2608
194.7 IPS |
|
|
Object Detection (F16)
|
100% |
2600
194.1 IPS |
|
|
Object Detection (I8)
|
60% |
2286
170.6 IPS |
|
|
Face Detection (F32)
|
100% |
5859
69.7 IPS |
|
|
Face Detection (F16)
|
100% |
5715
67.9 IPS |
|
|
Face Detection (I8)
|
89% |
4700
55.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
13359
103.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
13270
102.9 IPS |
|
|
Depth Estimation (I8)
|
95% |
10776
83.6 IPS |
|
|
Style Transfer (F32)
|
100% |
41482
54.6 IPS |
|
|
Style Transfer (F16)
|
100% |
40734
53.6 IPS |
|
|
Style Transfer (I8)
|
98% |
34880
45.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
9519
340.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
6195
221.3 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
5247
187.4 IPS |
|
|
Text Classification (F32)
|
100% |
1242
1.78 KIPS |
|
|
Text Classification (F16)
|
100% |
1622
2.33 KIPS |
|
|
Text Classification (I8)
|
98% |
882
1.27 KIPS |
|
|
Machine Translation (F32)
|
100% |
2078
38.2 IPS |
|
|
Machine Translation (F16)
|
100% |
2085
38.4 IPS |
|
|
Machine Translation (I8)
|
70% |
1044
19.2 IPS |
