AMD MAPLE
Geekbench ML Score
14546
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | July 24 2025 12:46 PM |
| Views | 8 |
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% |
7755
1.45 KIPS |
|
|
Image Classification (F16)
|
100% |
8301
1.55 KIPS |
|
|
Image Classification (I8)
|
100% |
7440
1.39 KIPS |
|
|
Image Segmentation (F32)
|
100% |
8650
144.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
11939
199.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
11216
187.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
78580
95.2 IPS |
|
|
Pose Estimation (F16)
|
100% |
69961
84.7 IPS |
|
|
Pose Estimation (I8)
|
100% |
65079
78.8 IPS |
|
|
Object Detection (F32)
|
100% |
3465
258.7 IPS |
|
|
Object Detection (F16)
|
100% |
2946
219.9 IPS |
|
|
Object Detection (I8)
|
62% |
3449
257.5 IPS |
|
|
Face Detection (F32)
|
100% |
19921
236.9 IPS |
|
|
Face Detection (F16)
|
100% |
19853
236.1 IPS |
|
|
Face Detection (I8)
|
89% |
14906
177.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
33528
260.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
30052
233.1 IPS |
|
|
Depth Estimation (I8)
|
95% |
24791
192.3 IPS |
|
|
Style Transfer (F32)
|
100% |
124607
163.9 IPS |
|
|
Style Transfer (F16)
|
100% |
124325
163.5 IPS |
|
|
Style Transfer (I8)
|
98% |
118578
156.0 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
24670
881.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
25210
900.3 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
20421
729.3 IPS |
|
|
Text Classification (F32)
|
100% |
3289
4.73 KIPS |
|
|
Text Classification (F16)
|
100% |
3797
5.46 KIPS |
|
|
Text Classification (I8)
|
98% |
2640
3.79 KIPS |
|
|
Machine Translation (F32)
|
100% |
5206
95.8 IPS |
|
|
Machine Translation (F16)
|
100% |
5767
106.1 IPS |
|
|
Machine Translation (I8)
|
70% |
3211
59.1 IPS |
