Razer Blade 14 - RZ09-0508
Geekbench ML Score
5098
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 27 2024 07:29 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | Razer Blade 14 - RZ09-0508 |
| Motherboard | PI4100 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 9 8945HS |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | AuthenticAMD Family 25 Model 117 Stepping 2 |
| Base Frequency | 4.00 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 | 32.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | AMD Radeon 780M Graphics |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
2181
408.1 IPS |
|
|
Image Classification (F16)
|
100% |
2171
406.2 IPS |
|
|
Image Classification (I8)
|
100% |
1922
359.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
2831
47.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
2826
47.2 IPS |
|
|
Image Segmentation (I8)
|
98% |
2400
40.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
37986
46.0 IPS |
|
|
Pose Estimation (F16)
|
100% |
36021
43.6 IPS |
|
|
Pose Estimation (I8)
|
100% |
27548
33.4 IPS |
|
|
Object Detection (F32)
|
100% |
1872
139.8 IPS |
|
|
Object Detection (F16)
|
100% |
1846
137.8 IPS |
|
|
Object Detection (I8)
|
62% |
1770
132.1 IPS |
|
|
Face Detection (F32)
|
100% |
5226
62.1 IPS |
|
|
Face Detection (F16)
|
100% |
5261
62.6 IPS |
|
|
Face Detection (I8)
|
89% |
4153
49.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
14984
116.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
14932
115.8 IPS |
|
|
Depth Estimation (I8)
|
95% |
12181
94.5 IPS |
|
|
Style Transfer (F32)
|
100% |
31941
42.0 IPS |
|
|
Style Transfer (F16)
|
100% |
30690
40.4 IPS |
|
|
Style Transfer (I8)
|
98% |
25812
34.0 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
5990
213.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
6159
219.9 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
4549
162.5 IPS |
|
|
Text Classification (F32)
|
100% |
1715
2.46 KIPS |
|
|
Text Classification (F16)
|
100% |
1794
2.58 KIPS |
|
|
Text Classification (I8)
|
98% |
1411
2.03 KIPS |
|
|
Machine Translation (F32)
|
100% |
2185
40.2 IPS |
|
|
Machine Translation (F16)
|
100% |
2169
39.9 IPS |
|
|
Machine Translation (I8)
|
70% |
1525
28.1 IPS |
