Razer Blade 16 - RZ09-0528
Geekbench AI Score
26372
Single Precision Score
45733
Half Precision Score
20387
Quantized Score
Geekbench AI 1.4.0 for Windows AVX2
Result Information
| Upload Date | August 20 2025 06:59 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 5080 Laptop GPU |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | Razer Blade 16 - RZ09-0528 |
| Motherboard | Razer SO6110 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | AMD Ryzen AI 9 365 |
| Topology | 1 Processor, 10 Cores, 20 Threads |
| Identifier | AuthenticAMD Family 26 Model 36 Stepping 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 6 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
11418
2.12 KIPS |
|
|
Image Classification (HP)
|
100% |
17602
3.27 KIPS |
|
|
Image Classification (Q)
|
100% |
10309
1.92 KIPS |
|
|
Image Segmentation (SP)
|
100% |
19215
311.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
28291
458.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
17577
285.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
137703
160.7 IPS |
|
|
Pose Estimation (HP)
|
100% |
401932
469.0 IPS |
|
|
Pose Estimation (Q)
|
96% |
120073
140.6 IPS |
|
|
Object Detection (SP)
|
100% |
13855
1.10 KIPS |
|
|
Object Detection (HP)
|
100% |
22884
1.82 KIPS |
|
|
Object Detection (Q)
|
86% |
11859
952.8 IPS |
|
|
Face Detection (SP)
|
100% |
39312
467.1 IPS |
|
|
Face Detection (HP)
|
100% |
56503
671.4 IPS |
|
|
Face Detection (Q)
|
97% |
32827
391.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
64062
493.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
123570
952.0 IPS |
|
|
Depth Estimation (Q)
|
78% |
51385
410.5 IPS |
|
|
Style Transfer (SP)
|
100% |
217731
279.9 IPS |
|
|
Style Transfer (HP)
|
100% |
778436
1.00 KIPS |
|
|
Style Transfer (Q)
|
98% |
188056
242.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
37244
1.38 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
67423
2.49 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
30005
1.11 KIPS |
|
|
Text Classification (SP)
|
100% |
3388
4.52 KIPS |
|
|
Text Classification (HP)
|
100% |
4171
5.57 KIPS |
|
|
Text Classification (Q)
|
97% |
2096
2.81 KIPS |
|
|
Machine Translation (SP)
|
100% |
5620
96.8 IPS |
|
|
Machine Translation (HP)
|
100% |
5717
98.5 IPS |
|
|
Machine Translation (Q)
|
70% |
2410
45.2 IPS |
