MAINGEAR ML16 MK.II
Geekbench ML Score
3123
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | July 25 2024 08:07 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | MAINGEAR ML16 MK.II |
| Motherboard | MAINGEAR V5xTNC_TND_TNE |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core Ultra 7 155H |
| Topology | 1 Processor, 16 Cores, 22 Threads |
| Identifier | GenuineIntel Family 6 Model 170 Stepping 4 |
| Base Frequency | 1.40 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 10 Cores |
| L1 Instruction Cache | 64.0 KB x 11 |
| L1 Data Cache | 48.0 KB x 11 |
| L2 Cache | 2.00 MB x 2 |
| L3 Cache | 24.0 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% |
1594
298.3 IPS |
|
|
Image Classification (F16)
|
100% |
1578
295.3 IPS |
|
|
Image Classification (I8)
|
99% |
2764
517.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
1521
25.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
1340
22.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
2557
42.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
6049
7.33 IPS |
|
|
Pose Estimation (F16)
|
100% |
5689
6.89 IPS |
|
|
Pose Estimation (I8)
|
100% |
21055
25.5 IPS |
|
|
Object Detection (F32)
|
100% |
1654
123.5 IPS |
|
|
Object Detection (F16)
|
100% |
1626
121.4 IPS |
|
|
Object Detection (I8)
|
62% |
1477
110.3 IPS |
|
|
Face Detection (F32)
|
100% |
3309
39.3 IPS |
|
|
Face Detection (F16)
|
100% |
3402
40.5 IPS |
|
|
Face Detection (I8)
|
89% |
3556
42.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
6673
51.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
6688
51.9 IPS |
|
|
Depth Estimation (I8)
|
96% |
13048
101.2 IPS |
|
|
Style Transfer (F32)
|
100% |
13751
18.1 IPS |
|
|
Style Transfer (F16)
|
100% |
13834
18.2 IPS |
|
|
Style Transfer (I8)
|
98% |
17219
22.7 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2617
93.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2696
96.3 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
4213
150.4 IPS |
|
|
Text Classification (F32)
|
100% |
1091
1.57 KIPS |
|
|
Text Classification (F16)
|
100% |
1094
1.57 KIPS |
|
|
Text Classification (I8)
|
98% |
394
566.0 IPS |
|
|
Machine Translation (F32)
|
100% |
1588
29.2 IPS |
|
|
Machine Translation (F16)
|
100% |
1558
28.7 IPS |
|
|
Machine Translation (I8)
|
67% |
2503
46.1 IPS |
