Ninkear M7
Geekbench ML Score
2023
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | September 11 2025 05:31 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Ninkear M7 |
| Motherboard | Ninkear M7 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 5 7430U with Radeon Graphics |
| Topology | 1 Processor, 6 Cores, 12 Threads |
| Identifier | AuthenticAMD Family 25 Model 80 Stepping 0 |
| Base Frequency | 2.30 GHz |
| Cluster 1 | 6 Cores |
| L1 Instruction Cache | 32.0 KB x 6 |
| L1 Data Cache | 32.0 KB x 6 |
| L2 Cache | 512 KB x 6 |
| L3 Cache | 16.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1170
218.9 IPS |
|
|
Image Classification (F16)
|
100% |
1163
217.7 IPS |
|
|
Image Classification (I8)
|
97% |
2072
387.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
1031
17.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
1017
17.0 IPS |
|
|
Image Segmentation (I8)
|
97% |
1714
28.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
3279
3.97 IPS |
|
|
Pose Estimation (F16)
|
100% |
3270
3.96 IPS |
|
|
Pose Estimation (I8)
|
100% |
6812
8.25 IPS |
|
|
Object Detection (F32)
|
100% |
1104
82.5 IPS |
|
|
Object Detection (F16)
|
100% |
1065
79.5 IPS |
|
|
Object Detection (I8)
|
60% |
1155
86.2 IPS |
|
|
Face Detection (F32)
|
100% |
1166
13.9 IPS |
|
|
Face Detection (F16)
|
100% |
1161
13.8 IPS |
|
|
Face Detection (I8)
|
87% |
2248
26.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
3585
27.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
3597
27.9 IPS |
|
|
Depth Estimation (I8)
|
74% |
6041
46.8 IPS |
|
|
Style Transfer (F32)
|
100% |
7612
10.0 IPS |
|
|
Style Transfer (F16)
|
100% |
7705
10.1 IPS |
|
|
Style Transfer (I8)
|
85% |
8134
10.7 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1688
60.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1637
58.5 IPS |
|
|
Image Super-Resolution (I8)
|
97% |
2036
72.7 IPS |
|
|
Text Classification (F32)
|
100% |
1290
1.85 KIPS |
|
|
Text Classification (F16)
|
100% |
1299
1.87 KIPS |
|
|
Text Classification (I8)
|
94% |
1027
1.48 KIPS |
|
|
Machine Translation (F32)
|
100% |
1286
23.7 IPS |
|
|
Machine Translation (F16)
|
100% |
1296
23.9 IPS |
|
|
Machine Translation (I8)
|
67% |
1668
30.7 IPS |
