Micro-Star International Co., Ltd. Katana 17 HX B14WFK
Geekbench ML Score
14451
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | August 26 2025 09:28 AM |
| Views | 6 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home Single Language (64-bit) |
| Model | Micro-Star International Co., Ltd. Katana 17 HX B14WFK |
| Motherboard | Micro-Star International Co., Ltd. MS-17L7 |
| 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 |
| L1 Instruction Cache | 32.0 KB x 16 |
| L1 Data Cache | 48.0 KB x 16 |
| L2 Cache | 2.00 MB x 4 |
| L3 Cache | 36.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 5060 Laptop GPU |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
6460
1.21 KIPS |
|
|
Image Classification (F16)
|
100% |
6126
1.15 KIPS |
|
|
Image Classification (I8)
|
100% |
5713
1.07 KIPS |
|
|
Image Segmentation (F32)
|
100% |
10409
173.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
10050
167.8 IPS |
|
|
Image Segmentation (I8)
|
98% |
9569
159.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
80558
97.6 IPS |
|
|
Pose Estimation (F16)
|
100% |
81016
98.1 IPS |
|
|
Pose Estimation (I8)
|
100% |
75360
91.3 IPS |
|
|
Object Detection (F32)
|
100% |
6003
448.1 IPS |
|
|
Object Detection (F16)
|
100% |
6029
450.1 IPS |
|
|
Object Detection (I8)
|
60% |
5555
414.7 IPS |
|
|
Face Detection (F32)
|
100% |
18883
224.5 IPS |
|
|
Face Detection (F16)
|
100% |
19256
229.0 IPS |
|
|
Face Detection (I8)
|
89% |
16228
193.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
41544
322.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
41252
319.9 IPS |
|
|
Depth Estimation (I8)
|
94% |
36106
280.0 IPS |
|
|
Style Transfer (F32)
|
100% |
128477
169.0 IPS |
|
|
Style Transfer (F16)
|
100% |
125380
164.9 IPS |
|
|
Style Transfer (I8)
|
98% |
108717
143.0 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
24198
864.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
23901
853.6 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
19384
692.3 IPS |
|
|
Text Classification (F32)
|
100% |
2888
4.15 KIPS |
|
|
Text Classification (F16)
|
100% |
3100
4.46 KIPS |
|
|
Text Classification (I8)
|
98% |
1937
2.78 KIPS |
|
|
Machine Translation (F32)
|
100% |
3650
67.2 IPS |
|
|
Machine Translation (F16)
|
100% |
3570
65.7 IPS |
|
|
Machine Translation (I8)
|
70% |
1729
31.8 IPS |
