Ninkear S14
Geekbench ML Score
2291
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | October 21 2025 02:16 PM |
| Views | 7 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Ninkear S14 |
| Motherboard | Ninkear Standard |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 5 7535HS |
| Topology | 1 Processor, 6 Cores, 12 Threads |
| Identifier | AuthenticAMD Family 25 Model 68 Stepping 1 |
| Base Frequency | 3.30 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% |
1509
282.3 IPS |
|
|
Image Classification (F16)
|
100% |
1489
278.6 IPS |
|
|
Image Classification (I8)
|
97% |
2033
380.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
411
6.86 IPS |
|
|
Image Segmentation (F16)
|
100% |
427
7.13 IPS |
|
|
Image Segmentation (I8)
|
97% |
1971
32.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
4283
5.19 IPS |
|
|
Pose Estimation (F16)
|
100% |
4281
5.18 IPS |
|
|
Pose Estimation (I8)
|
100% |
8092
9.80 IPS |
|
|
Object Detection (F32)
|
100% |
1415
105.6 IPS |
|
|
Object Detection (F16)
|
100% |
1399
104.4 IPS |
|
|
Object Detection (I8)
|
60% |
1369
102.2 IPS |
|
|
Face Detection (F32)
|
100% |
1928
22.9 IPS |
|
|
Face Detection (F16)
|
100% |
1932
23.0 IPS |
|
|
Face Detection (I8)
|
87% |
2948
35.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
4792
37.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
4784
37.1 IPS |
|
|
Depth Estimation (I8)
|
74% |
7285
56.5 IPS |
|
|
Style Transfer (F32)
|
100% |
9505
12.5 IPS |
|
|
Style Transfer (F16)
|
100% |
8559
11.3 IPS |
|
|
Style Transfer (I8)
|
85% |
10812
14.2 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1726
61.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1647
58.8 IPS |
|
|
Image Super-Resolution (I8)
|
97% |
2122
75.8 IPS |
|
|
Text Classification (F32)
|
100% |
1328
1.91 KIPS |
|
|
Text Classification (F16)
|
100% |
1335
1.92 KIPS |
|
|
Text Classification (I8)
|
94% |
1116
1.60 KIPS |
|
|
Machine Translation (F32)
|
100% |
1557
28.7 IPS |
|
|
Machine Translation (F16)
|
100% |
1656
30.5 IPS |
|
|
Machine Translation (I8)
|
67% |
2018
37.1 IPS |
