Razer Blade 16 - RZ09-0528
Geekbench AI Score
15228
Single Precision Score
27950
Half Precision Score
28860
Quantized Score
Geekbench AI 1.5.0 for Windows AVX2
Result Information
| User | springkim |
| Upload Date | October 28 2025 02:09 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | GPU |
| Device | Intel(R) Arc(TM) B580 Graphics (dGPU) |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Razer Blade 16 - RZ09-0528 |
| Motherboard | Razer SO6110 |
| CPU Information | |
|---|---|
| Name | AMD Ryzen AI 9 HX 370 |
| Topology | 1 Processor, 12 Cores, 24 Threads |
| Identifier | AuthenticAMD Family 26 Model 36 Stepping 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
6896
1.28 KIPS |
|
|
Image Classification (HP)
|
100% |
13742
2.56 KIPS |
|
|
Image Classification (Q)
|
100% |
17140
3.19 KIPS |
|
|
Image Segmentation (SP)
|
100% |
10110
163.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
13646
221.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
14273
231.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
75416
88.0 IPS |
|
|
Pose Estimation (HP)
|
100% |
284713
332.2 IPS |
|
|
Pose Estimation (Q)
|
97% |
500555
586.0 IPS |
|
|
Object Detection (SP)
|
100% |
5662
449.1 IPS |
|
|
Object Detection (HP)
|
100% |
14166
1.12 KIPS |
|
|
Object Detection (Q)
|
88% |
15763
1.26 KIPS |
|
|
Face Detection (SP)
|
100% |
15027
178.5 IPS |
|
|
Face Detection (HP)
|
100% |
28050
333.3 IPS |
|
|
Face Detection (Q)
|
100% |
34913
414.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
48149
371.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
94673
729.4 IPS |
|
|
Depth Estimation (Q)
|
89% |
97573
758.8 IPS |
|
|
Style Transfer (SP)
|
100% |
138223
177.7 IPS |
|
|
Style Transfer (HP)
|
100% |
423699
544.7 IPS |
|
|
Style Transfer (Q)
|
98% |
492783
635.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
27765
1.03 KIPS |
|
|
Image Super-Resolution (HP)
|
100% |
50233
1.85 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
34951
1.29 KIPS |
|
|
Text Classification (SP)
|
100% |
3012
4.02 KIPS |
|
|
Text Classification (HP)
|
100% |
2925
3.90 KIPS |
|
|
Text Classification (Q)
|
92% |
1744
2.34 KIPS |
|
|
Machine Translation (SP)
|
100% |
2694
46.4 IPS |
|
|
Machine Translation (HP)
|
98% |
2327
40.2 IPS |
|
|
Machine Translation (Q)
|
100% |
2030
35.0 IPS |
