InfraSight AI Platform

Discover AI Solutions

Guided, hands-on workflows to explore and select AI models with Jupyter Notebook tutorials on embedded platforms, Vitis, MIGraphX, ROCm & Vulkan.

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Explore Applications

Explore AI applications across Smart Infra, Machine Vision, and Smart Retail verticals with ready-to-deploy models.

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Explore Models

Find the right AI model for your use case with our interactive model comparison and selection tool.

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A + A Ref Design

Access AMD + Advantech reference designs for rapid prototyping and production-ready AI solutions.

Coming Soon

Ryzen AI Conversion

Step-by-step guides to convert and optimize your AI models for Ryzen AI hardware acceleration.

Device Specifications

Purpose-built Ryzen AI processors for high-performance edge inference, supported via Vitis, MIGraphX, ROCm & Vulkan runtimes.

Strix Point / P100
Ryzen AI 300 Series
NPU Performance50 TOPS
CPU CoresUp to 12C / 24T
iGPURadeon 800M
Best ForMainstream Edge AI
Strix Halo / X100
Ryzen AI Max Series
NPU Performance50 TOPS
CPU CoresUp to 16C / 32T
iGPURadeon 8060S
Best ForHigh-perf Workstation AI
R8000
Embedded Series
NPU Performance16 TOPS
CPU CoresUp to 8C / 16T
iGPURadeon 740M
Best ForEmbedded & IoT Edge

iGPU vs NPU

Ryzen AI devices feature both integrated GPU and a dedicated Neural Processing Unit. Here's how they compare.

iGPU
Integrated Graphics Processing Unit
  • Massively parallel compute for graphics & general-purpose AI workloads
  • Supports ONNX and Vulkan-based inference
  • Higher throughput for large batch sizes and vision models
  • Shared memory with CPU for zero-copy data transfer
NPU
Neural Processing Unit (XDNA)
  • Dedicated AI accelerator with ultra-low power consumption
  • Up to 50 TOPS for sustained, always-on AI inference
  • Optimized for INT8/INT4 quantized models and transformers
  • Frees GPU & CPU for other tasks during AI workloads