AMD MAPLE
Geekbench ML Score
14731
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | December 16 2025 06:40 AM |
| Views | 6 |
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% |
8732
1.63 KIPS |
|
|
Image Classification (F16)
|
100% |
8513
1.59 KIPS |
|
|
Image Classification (I8)
|
100% |
7449
1.39 KIPS |
|
|
Image Segmentation (F32)
|
100% |
12849
214.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
12657
211.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
10884
181.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
70238
85.1 IPS |
|
|
Pose Estimation (F16)
|
100% |
68787
83.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
60675
73.5 IPS |
|
|
Object Detection (F32)
|
100% |
3508
261.9 IPS |
|
|
Object Detection (F16)
|
100% |
3458
258.2 IPS |
|
|
Object Detection (I8)
|
62% |
3449
257.5 IPS |
|
|
Face Detection (F32)
|
100% |
17525
208.4 IPS |
|
|
Face Detection (F16)
|
100% |
17108
203.4 IPS |
|
|
Face Detection (I8)
|
89% |
14609
173.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
28092
217.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
33837
262.4 IPS |
|
|
Depth Estimation (I8)
|
95% |
25748
199.7 IPS |
|
|
Style Transfer (F32)
|
100% |
133250
175.3 IPS |
|
|
Style Transfer (F16)
|
100% |
128745
169.4 IPS |
|
|
Style Transfer (I8)
|
98% |
109488
144.0 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
25005
893.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
23709
846.7 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
19639
701.4 IPS |
|
|
Text Classification (F32)
|
100% |
3609
5.19 KIPS |
|
|
Text Classification (F16)
|
100% |
3681
5.29 KIPS |
|
|
Text Classification (I8)
|
98% |
2705
3.89 KIPS |
|
|
Machine Translation (F32)
|
100% |
5748
105.8 IPS |
|
|
Machine Translation (F16)
|
100% |
5789
106.5 IPS |
|
|
Machine Translation (I8)
|
70% |
3311
60.9 IPS |
