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AMD GAIA makes it easier to set up local AI agents and chat workflows on Ryzen AI 300-series PCs, but it is a software framework—not a guarantee that every model will run quickly or fit every computer. GAIA provides the agent and desktop experience; Lemonade Server manages models and inference backends. Ryzen AI 300 systems can use GPU/CPU, hybrid NPU+iGPU, or NPU-only execution, subject to the model and setup.
What GAIA does—and what it does not
GAIA is an open-source framework for running AI agents locally. Its current feature set includes a chat and desktop interface, tool orchestration, file browsing and document indexing, retrieval-augmented generation (RAG), voice integration, and vision-model support. AMD introduced GAIA as part of its Ryzen AI software work; its current capabilities and hardware requirements are documented in the GAIA repository and feature reference.
GAIA does not itself make all LLMs compatible with a PC or determine how quickly they run. It uses Lemonade Server to manage models and inference. The current feature reference describes GGUF models running through llama.cpp on GPU or CPU, and FLM-format models running on the Ryzen AI NPU. The repository also documents chat, coding, RAG, vision, and NPU setup profiles; available models and defaults can change as the project evolves.
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Check whether your Ryzen AI PC is a fit
The current GAIA repository lists Ryzen AI 300-series as its minimum processor, Windows 11 or Linux as supported operating systems, and 16 GB RAM minimum. It recommends a Ryzen AI Max+ 395 processor and 64 GB RAM. These are project-level requirements, not a promise that every model or workload will fit or perform well at the minimum specification.
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| Processor generation | Documented execution modes | What that means for GAIA |
|---|---|---|
| Ryzen AI 300 (STX/KRK) | NPU-only, hybrid NPU+iGPU, and GPU/CPU | Can use the NPU path when the additional software, driver, and model requirements are met. |
| Ryzen AI 7000/8000 | GPU/CPU only | Do not assume NPU support from the Ryzen AI name alone; AMD’s deployment overview lists these generations for GPU/CPU mode. |
These modes come from AMD’s Ryzen AI LLM Deployment Overview. The Ryzen AI software stack also offers Lemonade Python APIs or a server interface, alongside native ONNX Runtime GenAI and llama.cpp paths. AMD lists model families including Llama-2, Llama-3, Mistral, DeepSeek Distill, Qwen-2, Qwen-2.5, Qwen-3, Gemma-2, Phi-3, Phi-3.5, and Phi-4 as pre-optimized options. That collection is not the same as GAIA’s own current default model list.
Using GAIA’s NPU path
For NPU execution, GAIA’s guide specifies FastFlowLM (FLM). It lists Ryzen AI 300, 400, and Max processors with XDNA2, Lemonade Server v10.2.0 or later, and an AMD NPU driver with firmware v1.1.0.0 or later. These are the versions stated in the current guide and may change; check the live GAIA NPU guide before installing.
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The same guide excludes Ryzen AI 7000, 8000, and 200-series XDNA1 processors from FastFlowLM support and directs users of those systems to the GPU device path. In practice, confirm the exact processor generation and NPU architecture rather than relying on a laptop’s Ryzen AI branding.
Set up local chat and keep cloud use distinct
- Confirm the PC meets GAIA’s current requirements. Check its processor generation, operating system, and installed RAM against the repository requirements. If you specifically want NPU execution, also check the processor and software prerequisites in the NPU guide.
- Install and configure GAIA with Lemonade Server. GAIA’s documented model workflows use Lemonade Server to select and run models; choose a profile that matches the job, such as chat, coding, RAG, vision, or NPU use. Follow the repository’s current installation instructions, since setup details can change.
- Select a compatible model and execution device. GAIA’s feature reference distinguishes GGUF models for llama.cpp on GPU/CPU from FLM models for the NPU. Do not treat AMD’s broader pre-optimized model families as a guarantee that every model is a GAIA default or available in every execution mode.
- Choose local or cloud chat deliberately. Local inference is GAIA’s default. Its terminal interface also supports optional cloud chat providers; selecting one sends conversation history to that provider. Review the selected provider and configuration before using sensitive conversations.
What AMD’s newer software adds
In its January 26, 2026 release article for Ryzen AI Software 1.7, AMD reported support for GPT-OSS MoE and Gemma 3 4B VLM, integration of Stable Diffusion into the primary installer, and up to 16K tokens of context for most LLMs running in hybrid mode. AMD also reported approximately twice the BF16 throughput compared with Ryzen AI Software 1.6. That throughput figure is AMD’s claim, not an independent benchmark; see the Ryzen AI Software 1.7 release article for its stated context.
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