Best local AI models for AMD PRO W6300

The largest models that fit fully

The 30 largest of the 56 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 PRO W6300 is an entry level professional graphics card equipped with 2 GB of GDDR6 memory. This dedicated memory size determines which artificial intelligence models can run directly on the hardware. When a model fits entirely within this 2 GB limit, the graphics processor handles all calculations at maximum speed. If a model exceeds this capacity, it cannot run without transferring part of the workload to your system memory.

To make larger models fit into the limited memory of this card, developers use quantization. The quant column shows the specific compression level required to run each model. For example, the Allegro 2.8B model uses a Q4_K_M quantization to compress its parameters so it uses exactly 2 GB of memory. Smaller models like Moondream 2 can run at a higher quality Q6_K quantization while using 1.9 GB of memory. TinyLlama 1.1B runs at Q8_0 quantization using only 1.4 GB of memory.

When you run models that exceed the 2 GB limit, you must use CPU offload. This process splits the model between the graphics card and your system RAM. Running the 3B parameter SmolLM3 or Kandinsky 3.1 requires 2.2 GB of video memory at Q4_K_M quantization and an additional 4.2 GB of system RAM. Heavy models like Stable Diffusion XL require 4.1 GB of video memory at FP8 or optimized settings and 6.1 GB of system RAM.

CPU offload allows you to run larger tools like SDXL Turbo or MusicGen but it comes with a performance cost. Transferring data between your system RAM and the graphics card is much slower than using dedicated GDDR6 memory. Your generation speeds will drop significantly when the system RAM is active. For the best performance, choose models that fit completely within the 2 GB limit such as the 1.7B SmolLM2 or the 1.5B Whisper Large v2.

You must also consider the memory cost of context length. Running text models with a standard 4k context window increases the memory required during execution. The listed memory figures represent the base model size. If you generate long passages of text or process large prompts, the active memory usage will rise and may exceed the 2 GB limit of your AMD PRO W6300 card.