What hardware runs Llama 4 Scout?

Llama 4 Scout is a 107.77B-parameter mixture-of-experts model with 17.17B active parameters (other license). 17B active from 109B total, huge context on paper. Divisive reception; the long-document niche is where it earns keep.

All figures assume an f16 KV cache, a 0.6 GB display reserve on the GPU, and 64 GB of DDR5 system RAM for the offload tiers. Tune these in the calculator.

Minimum VRAM by quant and context

Full-GPU figures: weights + f16 KV cache + overhead. * below our recommended floor of Q3_K_M.

GPU compatibility

Fits on GPUExpert offloadPartial offloadCPU only

Quant guidance

Our floor for Llama 4 Scout is Q3_K_M — below that, quality degrades faster than the VRAM savings are worth (large models tolerate low bpw better than small ones, which is why the floor is lower here). Prefer the highest quant that still lands "Fits on GPU" or “Expert offload” at your context length in the table above.

Recommended run command

Q3_K_M at 32K on a NVIDIA GeForce RTX 5080-class GPU (Expert offload):

llama-server -m Llama-4-Scout-17B-16E-Instruct-Q3_K_M.gguf -c 32768 --flash-attn -ngl 99 --n-cpu-moe 48