Local AI Advisor

Can Desktop PC · GeForce RTX 5080 · 32 GB RAM run Llama 4 Scout (109B-A17B)?

16 GB VRAM + 32 GB RAM · 960 GB/s memory bandwidth · Llama 4 Scout (109B-A17B) has 108.6B parameters (17B active per token).

Short answer

No. It doesn't fit in memory.

Needs ≈52 GB but only ≈39 GB of VRAM + system RAM is available after the OS and other apps.

Why it doesn’t fit

Even its smallest practical version (Q3_K_M) needs about 52 GB for the model, its context memory and the runtime. After Windows (≈4.5 GB), a browser with a few tabs (≈3.0 GB) and Open WebUI (≈1.0 GB), Desktop PC · GeForce RTX 5080 · 32 GB RAM has about 39 GB left, so it’s 14 GB short.

Ways to make it work

  • Close everything else

    Not enough on its own: with every other app closed it’s still about 11 GB short.

  • Pick a smaller model from the same family

    No smaller Llama 4 model in our catalog runs well here. See the other models below.

  • Get more memory

    You’d want at least 61 GB of VRAM plus RAM in total. The machines below are the cheapest that run it comfortably.

  • Check your exact setup

    These pages assume typical settings. A shorter context or a lighter chat app can change the answer.

    Check Desktop PC · GeForce RTX 5080 · 32 GB RAM

The same applies to every workload we rate (chat, coding questions, coding in a repository, agentic coding and long documents): they all need at least as much memory as chat.

Different tool, context size or workload?

These pages use typical settings. The full check models your exact setup.

Open weights (restricted)Check my exact setup