What hardware do you need to run Llama 4 Scout 17B-16E?

Llama 4 Scout 17B-16E at Q4_K_M is 65 GB of weights, with a context ceiling of 10240k tokens. Enormous context on paper. Reception on quality-for-size was mixed; the 30B MoEs are usually the better buy.

How good is it, really?

On the Artificial Analysis Intelligence Index v4.3 it scores 6, which puts it in the Below every hosted tier band. Fine for simple, well-specified tasks. Noticeably less capable than anything the big labs sell today. Score source. See the whole table.

• Summarising — good
• Translation — good
• Everyday coding — usable
• Reasoning & maths — usable
• Agentic work — usable

What it costs either way

Renting the same model costs $0.1 per million input tokens and $0.3 per million output (OpenRouter, cheapest active endpoint, checked 2026-09-03). Buying a machine only beats that if you use it hard enough, for long enough, that the hardware price divides down below the rental bill.

Machines that run it

One machine per family, cheapest first. Speeds are measured where a public benchmark exists and estimated from memory bandwidth otherwise; the calculator says which for any configuration.

The specifics

Parameters

108.6B, of which 17B are active per token

Quantisation

Q4_K_M

Weights on disk

65 GB

KV cache

2.8 GB at 32k context — 36 of 48 layers use chunked attention with an 8192-token chunk; modelled here as a sliding window.

Maximum context

10240k tokens (10M claimed; nobody has the memory for that locally)

Licence

Llama 4 Community License

Sources

source 1, source 2