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Llama 3.1 405B Instruct

Llama 3.1 405B Instruct loads in 243 GB at Q4_K_M, comfortably from 256 GB of memory. Below is the memory math we ran for it, the cheapest card that fits, and the fastest machine we track.

PARAMETERS
405B
FORMAT
Q4_K_M
MIN MEMORY
320 GB
BEST FOR
Quality, Reasoning, Coding

How much memory does Llama 3.1 405B Instruct need?

Llama 3.1 405B Instruct is a 405B dense model built for quality, reasoning, coding. The weights alone take 243 GB at Q4_K_M; add context and the OS, and it belongs in the 256 GB memory class. Every number below comes from the ModelFit engine — speeds are estimates, labeled est., because we do not benchmark hardware ourselves.

Weights (Q4_K_M)
243 GB
+ KV cache (16k)
~6.0 GB
Total at 16k
~249.0 GB
Comfortable from
256 GB

KV = fp16 estimate (q8_0 cache roughly halves it). "Comfortable" = weights + KV within the engine's tiered budget (~70-85% of memory).

Which machines run Llama 3.1 405B Instruct?

Cheapest GPU
no consumer fit
Fastest
n/a
Runs on a Mac?
No
beyond current Macs

Verdicts come from the same engine that powers our fit checker — memory capacity first, bandwidth for speed. How we compute these numbers · Hugging Face model card

More Llama models

Frequently asked questions

How much memory does Llama 3.1 405B Instruct need?

243 GB for the Q4_K_M weights, plus ~6.0 GB of KV-cache at 16k context — about 249.0 GB total. Comfortable from 256 GB of VRAM or unified memory.

Does Llama 3.1 405B Instruct run on a Mac?

Not on the current Mac configs we track; Llama 3.1 405B Instruct needs more memory than they offer.

What is the cheapest GPU for Llama 3.1 405B Instruct?

No tracked consumer GPU runs Llama 3.1 405B Instruct comfortably.

Cite this page

ModelFit: Llama 3.1 405B Instruct — specs, memory math and hardware verdicts.
https://modelfit.io/models/llama-3.1-405b/ (dataset updated 2026-09-03, CC BY 4.0).