LENOVO 83FD
Geekbench ML Score
3794
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | February 18 2025 03:46 AM |
| Views | 6 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 (64-bit) |
| Model | LENOVO 83FD |
| Motherboard | LENOVO LNVNB161216 |
| CPU Information | |
|---|---|
| Name | Intel Core i9-14900HX |
| Topology | 1 Processor, 24 Cores, 32 Threads |
| Identifier | GenuineIntel Family 6 Model 183 Stepping 1 |
| Base Frequency | 2.20 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 16 Cores |
| L1 Instruction Cache | 64.0 KB x 16 |
| L1 Data Cache | 32.0 KB x 16 |
| L2 Cache | 4.00 MB x 4 |
| L3 Cache | 36.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
2022
378.3 IPS |
|
|
Image Classification (F16)
|
100% |
2116
396.0 IPS |
|
|
Image Classification (I8)
|
99% |
3289
615.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
1890
31.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
1826
30.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
2572
43.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
7707
9.33 IPS |
|
|
Pose Estimation (F16)
|
100% |
7835
9.49 IPS |
|
|
Pose Estimation (I8)
|
100% |
25535
30.9 IPS |
|
|
Object Detection (F32)
|
100% |
1984
148.1 IPS |
|
|
Object Detection (F16)
|
100% |
1824
136.1 IPS |
|
|
Object Detection (I8)
|
62% |
1615
120.6 IPS |
|
|
Face Detection (F32)
|
100% |
3324
39.5 IPS |
|
|
Face Detection (F16)
|
100% |
4045
48.1 IPS |
|
|
Face Detection (I8)
|
89% |
3934
46.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
8367
64.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
8092
62.8 IPS |
|
|
Depth Estimation (I8)
|
96% |
14715
114.1 IPS |
|
|
Style Transfer (F32)
|
100% |
19559
25.7 IPS |
|
|
Style Transfer (F16)
|
100% |
17610
23.2 IPS |
|
|
Style Transfer (I8)
|
98% |
22590
29.7 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3474
124.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
3861
137.9 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
4759
170.0 IPS |
|
|
Text Classification (F32)
|
100% |
1472
2.12 KIPS |
|
|
Text Classification (F16)
|
100% |
1484
2.13 KIPS |
|
|
Text Classification (I8)
|
98% |
400
574.6 IPS |
|
|
Machine Translation (F32)
|
100% |
1864
34.3 IPS |
|
|
Machine Translation (F16)
|
100% |
1924
35.4 IPS |
|
|
Machine Translation (I8)
|
67% |
2561
47.1 IPS |
