AMD MAPLE
Geekbench ML Score
14468
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | July 28 2025 12:41 PM |
| Views | 5 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | AMD MAPLE |
| Motherboard | AMD MAPLE-STXH |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | AMD Ryzen AI Max+ 395 |
| Topology | 1 Processor, 16 Cores, 32 Threads |
| Identifier | AuthenticAMD Family 26 Model 112 Stepping 0 |
| Base Frequency | 3.00 GHz |
| Cluster 1 | 16 Cores |
| L1 Instruction Cache | 32.0 KB x 16 |
| L1 Data Cache | 48.0 KB x 16 |
| L2 Cache | 1.00 MB x 16 |
| L3 Cache | 32.0 MB x 2 |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | AMD Radeon(TM) 8060S Graphics |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
7813
1.46 KIPS |
|
|
Image Classification (F16)
|
100% |
7396
1.38 KIPS |
|
|
Image Classification (I8)
|
100% |
6708
1.26 KIPS |
|
|
Image Segmentation (F32)
|
100% |
12093
202.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
11564
193.1 IPS |
|
|
Image Segmentation (I8)
|
98% |
11110
185.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
70747
85.7 IPS |
|
|
Pose Estimation (F16)
|
100% |
67024
81.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
62292
75.4 IPS |
|
|
Object Detection (F32)
|
100% |
3461
258.4 IPS |
|
|
Object Detection (F16)
|
100% |
3460
258.3 IPS |
|
|
Object Detection (I8)
|
62% |
3461
258.4 IPS |
|
|
Face Detection (F32)
|
100% |
17128
203.7 IPS |
|
|
Face Detection (F16)
|
100% |
20266
241.0 IPS |
|
|
Face Detection (I8)
|
89% |
15726
187.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
27999
217.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
30579
237.1 IPS |
|
|
Depth Estimation (I8)
|
95% |
28935
224.4 IPS |
|
|
Style Transfer (F32)
|
100% |
120147
158.0 IPS |
|
|
Style Transfer (F16)
|
100% |
114687
150.9 IPS |
|
|
Style Transfer (I8)
|
98% |
109117
143.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
23211
828.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
22768
813.1 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
20567
734.5 IPS |
|
|
Text Classification (F32)
|
100% |
3703
5.32 KIPS |
|
|
Text Classification (F16)
|
100% |
3870
5.56 KIPS |
|
|
Text Classification (I8)
|
98% |
2697
3.88 KIPS |
|
|
Machine Translation (F32)
|
100% |
5679
104.5 IPS |
|
|
Machine Translation (F16)
|
100% |
5532
101.8 IPS |
|
|
Machine Translation (I8)
|
70% |
3287
60.5 IPS |
