AMD MAPLE
Geekbench ML Score
14770
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | March 11 2026 09:32 AM |
| Views | 9 |
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% |
7651
1.43 KIPS |
|
|
Image Classification (F16)
|
100% |
8364
1.57 KIPS |
|
|
Image Classification (I8)
|
100% |
7663
1.43 KIPS |
|
|
Image Segmentation (F32)
|
100% |
9212
153.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
12539
209.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
11281
188.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
75480
91.4 IPS |
|
|
Pose Estimation (F16)
|
100% |
69543
84.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
62755
76.0 IPS |
|
|
Object Detection (F32)
|
100% |
3515
262.4 IPS |
|
|
Object Detection (F16)
|
100% |
3419
255.2 IPS |
|
|
Object Detection (I8)
|
62% |
3746
279.6 IPS |
|
|
Face Detection (F32)
|
100% |
19566
232.6 IPS |
|
|
Face Detection (F16)
|
100% |
19715
234.4 IPS |
|
|
Face Detection (I8)
|
89% |
14855
176.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
34566
268.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
33202
257.5 IPS |
|
|
Depth Estimation (I8)
|
95% |
29853
231.5 IPS |
|
|
Style Transfer (F32)
|
100% |
135972
178.9 IPS |
|
|
Style Transfer (F16)
|
100% |
134009
176.3 IPS |
|
|
Style Transfer (I8)
|
98% |
116239
152.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
22286
795.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
23997
857.0 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
19695
703.4 IPS |
|
|
Text Classification (F32)
|
100% |
3167
4.55 KIPS |
|
|
Text Classification (F16)
|
100% |
3873
5.57 KIPS |
|
|
Text Classification (I8)
|
98% |
2671
3.84 KIPS |
|
|
Machine Translation (F32)
|
100% |
4967
91.4 IPS |
|
|
Machine Translation (F16)
|
100% |
5750
105.8 IPS |
|
|
Machine Translation (I8)
|
70% |
3110
57.2 IPS |
