Micro-Star International Co., Ltd. Vector A16 HX A8WHG
Geekbench ML Score
20920
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | October 10 2025 04:09 PM |
| Views | 6 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home Single Language (64-bit) |
| Model | Micro-Star International Co., Ltd. Vector A16 HX A8WHG |
| Motherboard | Micro-Star International Co., Ltd. MS-15MM |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | AMD Ryzen 9 8940HX with Radeon Graphics |
| Topology | 1 Processor, 16 Cores, 32 Threads |
| Identifier | AuthenticAMD Family 25 Model 97 Stepping 2 |
| Base Frequency | 2.40 GHz |
| Cluster 1 | 16 Cores |
| L1 Instruction Cache | 32.0 KB x 16 |
| L1 Data Cache | 32.0 KB x 16 |
| L2 Cache | 1.00 MB x 16 |
| L3 Cache | 32.0 MB x 2 |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 5070 Ti Laptop GPU |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
9811
1.84 KIPS |
|
|
Image Classification (F16)
|
100% |
9747
1.82 KIPS |
|
|
Image Classification (I8)
|
100% |
8716
1.63 KIPS |
|
|
Image Segmentation (F32)
|
100% |
15827
264.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
15885
265.3 IPS |
|
|
Image Segmentation (I8)
|
98% |
14561
243.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
123242
149.2 IPS |
|
|
Pose Estimation (F16)
|
100% |
123008
149.0 IPS |
|
|
Pose Estimation (I8)
|
100% |
121424
147.0 IPS |
|
|
Object Detection (F32)
|
100% |
7580
565.9 IPS |
|
|
Object Detection (F16)
|
100% |
7557
564.1 IPS |
|
|
Object Detection (I8)
|
57% |
7032
525.0 IPS |
|
|
Face Detection (F32)
|
100% |
31359
372.9 IPS |
|
|
Face Detection (F16)
|
100% |
31775
377.8 IPS |
|
|
Face Detection (I8)
|
89% |
26220
311.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
60362
468.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
61298
475.4 IPS |
|
|
Depth Estimation (I8)
|
94% |
50394
390.8 IPS |
|
|
Style Transfer (F32)
|
100% |
204930
269.6 IPS |
|
|
Style Transfer (F16)
|
100% |
204451
268.9 IPS |
|
|
Style Transfer (I8)
|
98% |
176696
232.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
35439
1.27 KIPS |
|
|
Image Super-Resolution (F16)
|
100% |
36268
1.30 KIPS |
|
|
Image Super-Resolution (I8)
|
99% |
29086
1.04 KIPS |
|
|
Text Classification (F32)
|
100% |
3316
4.77 KIPS |
|
|
Text Classification (F16)
|
100% |
3330
4.79 KIPS |
|
|
Text Classification (I8)
|
98% |
2134
3.07 KIPS |
|
|
Machine Translation (F32)
|
100% |
4967
91.4 IPS |
|
|
Machine Translation (F16)
|
100% |
4986
91.8 IPS |
|
|
Machine Translation (I8)
|
70% |
2325
42.8 IPS |
