Razer Blade 18 - RZ09-0509
Geekbench AI Score
23610
Single Precision Score
32735
Half Precision Score
17554
Quantized Score
Geekbench AI 1.0.0 for Windows AVX2
Result Information
| Upload Date | August 15 2024 04:00 PM |
| Views | 20 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 4090 Laptop GPU |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | Razer Blade 18 - RZ09-0509 |
| Motherboard | Razer KI8100 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i9-14900HX |
| Topology | 1 Processor, 24 Cores, 32 Threads |
| Identifier | GenuineIntel Family 6 Model 183 Stepping 1 |
| Base Frequency | 2.20 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 16 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
7319
1.36 KIPS |
|
|
Image Classification (HP)
|
99% |
11235
2.10 KIPS |
|
|
Image Classification (Q)
|
100% |
7031
1.31 KIPS |
|
|
Image Segmentation (SP)
|
100% |
14734
238.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
19540
316.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
13632
221.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
194901
227.4 IPS |
|
|
Pose Estimation (HP)
|
100% |
339753
396.4 IPS |
|
|
Pose Estimation (Q)
|
97% |
158084
185.1 IPS |
|
|
Object Detection (SP)
|
100% |
9349
741.6 IPS |
|
|
Object Detection (HP)
|
100% |
12412
984.5 IPS |
|
|
Object Detection (Q)
|
89% |
8389
671.6 IPS |
|
|
Face Detection (SP)
|
100% |
29260
347.7 IPS |
|
|
Face Detection (HP)
|
100% |
35591
422.9 IPS |
|
|
Face Detection (Q)
|
97% |
25136
299.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
54441
419.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
82457
635.3 IPS |
|
|
Depth Estimation (Q)
|
76% |
42483
342.6 IPS |
|
|
Style Transfer (SP)
|
100% |
304810
391.8 IPS |
|
|
Style Transfer (HP)
|
100% |
652928
839.3 IPS |
|
|
Style Transfer (Q)
|
98% |
263762
340.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
43067
1.59 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
52945
1.95 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
28098
1.04 KIPS |
|
|
Text Classification (SP)
|
100% |
3365
4.49 KIPS |
|
|
Text Classification (HP)
|
99% |
4261
5.69 KIPS |
|
|
Text Classification (Q)
|
97% |
1745
2.34 KIPS |
|
|
Machine Translation (SP)
|
100% |
3893
67.1 IPS |
|
|
Machine Translation (HP)
|
100% |
3531
60.8 IPS |
|
|
Machine Translation (Q)
|
60% |
1583
35.3 IPS |
