Razer Blade 15 Base Model (Early 2021) - RZ09-0369
Geekbench ML Score
1242
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | August 16 2024 08:44 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 10 Home (64-bit) |
| Model | Razer Blade 15 Base Model (Early 2021) - RZ09-0369 |
| Motherboard | Razer DA560 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i7-10750H |
| Topology | 1 Processor, 6 Cores, 12 Threads |
| Identifier | GenuineIntel Family 6 Model 165 Stepping 2 |
| Base Frequency | 2.59 GHz |
| Cluster 1 | 6 Cores |
| L1 Instruction Cache | 32.0 KB x 6 |
| L1 Data Cache | 32.0 KB x 6 |
| L2 Cache | 256 KB x 6 |
| L3 Cache | 12.0 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% |
775
145.0 IPS |
|
|
Image Classification (F16)
|
100% |
690
129.1 IPS |
|
|
Image Classification (I8)
|
97% |
1108
207.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
489
8.16 IPS |
|
|
Image Segmentation (F16)
|
100% |
542
9.06 IPS |
|
|
Image Segmentation (I8)
|
97% |
853
14.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
2052
2.49 IPS |
|
|
Pose Estimation (F16)
|
100% |
2030
2.46 IPS |
|
|
Pose Estimation (I8)
|
100% |
4178
5.06 IPS |
|
|
Object Detection (F32)
|
100% |
673
50.2 IPS |
|
|
Object Detection (F16)
|
100% |
719
53.7 IPS |
|
|
Object Detection (I8)
|
60% |
673
50.3 IPS |
|
|
Face Detection (F32)
|
100% |
1127
13.4 IPS |
|
|
Face Detection (F16)
|
100% |
720
8.56 IPS |
|
|
Face Detection (I8)
|
87% |
1751
20.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
1996
15.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
2271
17.6 IPS |
|
|
Depth Estimation (I8)
|
74% |
3570
27.7 IPS |
|
|
Style Transfer (F32)
|
100% |
5079
6.68 IPS |
|
|
Style Transfer (F16)
|
100% |
4986
6.56 IPS |
|
|
Style Transfer (I8)
|
85% |
7011
9.22 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1097
39.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1119
40.0 IPS |
|
|
Image Super-Resolution (I8)
|
97% |
1521
54.3 IPS |
|
|
Text Classification (F32)
|
100% |
766
1.10 KIPS |
|
|
Text Classification (F16)
|
100% |
735
1.06 KIPS |
|
|
Text Classification (I8)
|
94% |
258
370.1 IPS |
|
|
Machine Translation (F32)
|
100% |
886
16.3 IPS |
|
|
Machine Translation (F16)
|
100% |
840
15.5 IPS |
|
|
Machine Translation (I8)
|
67% |
1083
19.9 IPS |
