AZW MINI S
Geekbench ML Score
347
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows x86 (64-bit)
Result Information
| Upload Date | June 22 2025 09:15 AM |
| Views | 7 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | AZW MINI S |
| Motherboard | AZW MINI S |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel(R) Celeron(R) N5095A @ 2.00GHz |
| Topology | 1 Processor, 4 Cores |
| Identifier | GenuineIntel Family 6 Model 156 Stepping 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores |
| L1 Instruction Cache | 32.0 KB x 4 |
| L1 Data Cache | 32.0 KB x 4 |
| L2 Cache | 1.50 MB x 1 |
| L3 Cache | 4.00 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% |
184
34.5 IPS |
|
|
Image Classification (F16)
|
100% |
175
32.8 IPS |
|
|
Image Classification (I8)
|
96% |
293
54.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
172
2.88 IPS |
|
|
Image Segmentation (F16)
|
100% |
166
2.77 IPS |
|
|
Image Segmentation (I8)
|
97% |
347
5.79 IPS |
|
|
Pose Estimation (F32)
|
100% |
353
0.43 IPS |
|
|
Pose Estimation (F16)
|
100% |
360
0.44 IPS |
|
|
Pose Estimation (I8)
|
100% |
727
0.88 IPS |
|
|
Object Detection (F32)
|
100% |
179
13.3 IPS |
|
|
Object Detection (F16)
|
100% |
184
13.8 IPS |
|
|
Object Detection (I8)
|
62% |
218
16.3 IPS |
|
|
Face Detection (F32)
|
100% |
416
4.94 IPS |
|
|
Face Detection (F16)
|
100% |
418
4.96 IPS |
|
|
Face Detection (I8)
|
87% |
545
6.48 IPS |
|
|
Depth Estimation (F32)
|
100% |
509
3.95 IPS |
|
|
Depth Estimation (F16)
|
100% |
521
4.04 IPS |
|
|
Depth Estimation (I8)
|
74% |
880
6.82 IPS |
|
|
Style Transfer (F32)
|
100% |
950
1.25 IPS |
|
|
Style Transfer (F16)
|
100% |
943
1.24 IPS |
|
|
Style Transfer (I8)
|
85% |
1462
1.92 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
245
8.77 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
251
8.95 IPS |
|
|
Image Super-Resolution (I8)
|
97% |
439
15.7 IPS |
|
|
Text Classification (F32)
|
100% |
201
288.4 IPS |
|
|
Text Classification (F16)
|
100% |
199
285.6 IPS |
|
|
Text Classification (I8)
|
94% |
338
485.2 IPS |
|
|
Machine Translation (F32)
|
100% |
327
6.02 IPS |
|
|
Machine Translation (F16)
|
100% |
329
6.05 IPS |
|
|
Machine Translation (I8)
|
67% |
250
4.60 IPS |
