Best local AI models for AMD R9 M470X

The largest models that fit fully

The 30 largest of the 81 models that fit; every smaller model in the catalog fits too. Best quant means the highest quality compression whose weights and 4k context both sit inside the memory.

Close, but only with CPU offload

These need more than the card holds at their smallest practical quant, so part of the model runs from system memory (figures assume 32 GB of it). They work, several times slower.

How to read this

The AMD Radeon R9 M470X is a mobile graphics card equipped with 4 GB of GDDR5 memory. This dedicated video memory determines the maximum size of the artificial intelligence models you can run entirely on the hardware. To run a model smoothly without system slowdowns, the model files and the active memory space must fit within this 4 GB limit.

Quantization is a method that compresses model files to save space. The quant column shows the best compression format that fits your hardware. For example, the 5B Lumina-Next model fits at a Q4_K_M quantization using 3.7 GB of memory. Smaller models like the 3B SmolLM3 can run at a higher quality Q8_0 quantization because they only require 3.8 GB of memory.

Many capable models fit directly inside the graphics memory. You can run the 4.5B DeepSeek-VL2 model at Q5_K_M quantization using 3.8 GB of memory. For image generation, Stable Diffusion 3.5 Medium fits at Q8_0 quantization using 3.2 GB of memory. Audio models like Orpheus TTS also run locally using 3.8 GB of memory at Q8_0 quantization.

When a model is too large for the 4 GB graphics memory, you must use CPU offload. This process splits the model between your graphics card and your system RAM. For example, running the Mistral 7B model at Q4_K_M quantization requires 5.7 GB of memory, which uses 7.7 GB of system RAM. CPU offload makes larger models run but slows down the processing speed.

System RAM requirements increase when you offload models. Running the Qwen2.5 7B model at Q4_K_M quantization requires 5.1 GB of memory and needs 7.1 GB of system RAM. This setup assumes your computer has 32 GB of system RAM installed. Other models like Falcon 3 7B and Command R7B share these exact memory requirements.

Active context window size also affects your memory usage. Running models at a standard 4k context window length requires extra memory space. If you increase the context window to process longer documents, the model will require more memory than the base numbers listed here. You may need to use a lower quantization to avoid running out of memory.