Standard NA10H
Geekbench ML Score
3422
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | June 10 2025 08:36 PM |
| Views | 5 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | Standard NA10H |
| Motherboard | Standard NA10H |
| Power Plan | Gebalanceerd |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 7 8845HS |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | AuthenticAMD Family 25 Model 117 Stepping 2 |
| Base Frequency | 3.80 GHz |
| Cluster 1 | 8 Cores |
| L1 Instruction Cache | 32.0 KB x 8 |
| L1 Data Cache | 32.0 KB x 8 |
| L2 Cache | 1.00 MB x 8 |
| 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% |
1761
329.4 IPS |
|
|
Image Classification (F16)
|
100% |
1712
320.4 IPS |
|
|
Image Classification (I8)
|
99% |
3141
587.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
820
13.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
1006
16.8 IPS |
|
|
Image Segmentation (I8)
|
98% |
3261
54.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
7140
8.65 IPS |
|
|
Pose Estimation (F16)
|
100% |
7200
8.72 IPS |
|
|
Pose Estimation (I8)
|
100% |
24202
29.3 IPS |
|
|
Object Detection (F32)
|
100% |
1870
139.6 IPS |
|
|
Object Detection (F16)
|
100% |
1815
135.5 IPS |
|
|
Object Detection (I8)
|
62% |
2000
149.3 IPS |
|
|
Face Detection (F32)
|
100% |
1967
23.4 IPS |
|
|
Face Detection (F16)
|
100% |
1979
23.5 IPS |
|
|
Face Detection (I8)
|
89% |
3684
43.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
6978
54.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
7003
54.3 IPS |
|
|
Depth Estimation (I8)
|
96% |
15125
117.3 IPS |
|
|
Style Transfer (F32)
|
100% |
15377
20.2 IPS |
|
|
Style Transfer (F16)
|
100% |
15049
19.8 IPS |
|
|
Style Transfer (I8)
|
98% |
16227
21.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2917
104.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2744
98.0 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
3260
116.4 IPS |
|
|
Text Classification (F32)
|
100% |
2040
2.93 KIPS |
|
|
Text Classification (F16)
|
100% |
1943
2.79 KIPS |
|
|
Text Classification (I8)
|
98% |
1459
2.10 KIPS |
|
|
Machine Translation (F32)
|
100% |
1713
31.5 IPS |
|
|
Machine Translation (F16)
|
100% |
1716
31.6 IPS |
|
|
Machine Translation (I8)
|
67% |
2817
51.8 IPS |
