What hardware do you need to run Qwen3 14B?

Qwen3 14B at Q4_K_M is 9.0 GB of weights, with a context ceiling of 40k tokens. The sweet spot for a 24 GB machine. Everyday coding help is usable; long agent loops drift. On the cheapest machine that runs it, a Mac mini M6, 24GB, it generates 8.9 tok/s at 32k of context, worked out from memory bandwidth.

How good is Qwen3 14B, really?

On the Artificial Analysis Intelligence Index v4.3 it scores 6 (reasoning mode; 7 without), 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. See the whole table.

• Summarising — good
• Translation — good
• Everyday coding — usable
• Reasoning & maths — usable
• Agentic work — don’t

Head to head with its neighbours on the leaderboard: vs Mistral Small 3.2 24B Instruct above it, vs Llama 4 Scout 17B-16E below. One more model needs much the same memory at 32k of context: vs Ministral 3 14B.

Is Qwen3 14B still worth running?

Not on the two figures this site can compare. The intelligence index puts nine of the current models here above Qwen3 14B, and not one of them asks more of a machine: at 32k of context it needs 14.4 GB and scores 6 (reasoning mode; 7 without), where the strongest of the nine, Qwen3.5 9B, needs 6.8 GB and scores 14 (reasoning mode; 13 without).

The cheapest machine still sold that holds Qwen3 14B at 32k is the Mac mini M6, 24GB at $1,099, which holds Qwen3.5 9B as well. This site quotes Qwen3.5 9B at 19 tok/s estimated there and Qwen3 14B at 8.9 tok/s estimated. Qwen3.5 9B itself runs on the Mac mini M6, 16GB at $899, $200 less.

Qwen3.5 9B's score is Artificial Analysis's own estimate rather than a measured run of the full v4.3 suite.

What Qwen3 14B costs either way

Renting the same model costs $0.1 per million input tokens and $0.22 per million output (OpenRouter, cheapest active endpoint, checked 2026-10-29). 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. What a million tokens costs each way puts the two prices side by side.

Machines that run Qwen3 14B

Every machine here holds it to 32k, the longest setting below this model's own 40k limit, so the choice between them is speed and price rather than how much you can keep in the window.

The table is the cheapest machine in each family, not the only one that runs it: 50 of the 56 machines on this site hold it at 32k. Within a family only memory decides, so that is every Mac Studio and Strix Halo box at any size, every NVIDIA card with 16GB or more, every Mac mini and MacBook Pro with 24GB or more, the Radeon AI PRO R9700, 32GB and the DGX Spark, 128GB. One table sets every machine against the others: price, the memory its GPU can use, what it holds and how long it takes to pay for itself.

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 longest context is the longest setting the calculator offers that the machine still holds this model at, cache included, and no machine is shown taking it past its own 40k limit. Each one opens the calculator on that machine at that length.

For scale, the calculator starts from 80 tok/s for a hosted API and times a local machine against it. 1 of the 7 above reaches it, and the slowest is 8 tok/s.

The cheapest machine that runs it is sold with 24 GB. There is a page on what 24 GB runs, machine by machine: it names the 7 machines here sold at that size, and the 28 current models the roomiest of them holds at 32k.

It fits in less memory than that: the smallest size here that runs it at 32k is 16 GB, on the GeForce RTX 4080, 16GB at $1,199, card only, which hands a model 15 GB and is no longer sold.

What has been measured running Qwen3 14B

One of the speeds in the table above was measured, and there are more measurements than that table shows. Six machines here have a published speed for Qwen3 14B. The table above has one of them; the other five are no longer sold. They are below, as published and again at 32k of context, which is what every other speed on this page is taken at.

A published figure is what its source reports, at the window the model was run at. The 32k figure is that measurement read at 32k of context: every token generated reads the weights and the whole key-value cache, so the longer the window the slower it runs. Where a machine does not hold Qwen3 14B at 32k, the row gives the longest window it does hold. A discontinued machine's price is the one it launched at. Each published figure links the source that took it.

Three more machines, at a shorter window

The table above lists the machines that run it at 32k, the context the calculator starts on, where Qwen3 14B needs 14 GB. Three more machines hold it at a shorter window, because the weights are the same size either way and the key-value cache is not. The cheapest of those is the Mac mini M6, 16GB at $899. The table above starts at $1,099.

One machine per family, cheapest first, from the same list as the table above. Each window is the longest setting the calculator offers that the machine still holds this model at, and it opens the calculator on that machine at that length. What it needs there is the weights plus the key-value cache at that window, measured against the memory each machine's GPU can address, which that machine's own page gives.

The specifics

Parameters

14.8B

Quantisation

Q4_K_M

Weights on disk

9.0 GB

KV cache

5.4 GB at 32k context. How weights and cache add up.

Maximum context

40k tokens (32k natively; 128k with YaRN)

Licence

Apache 2.0

Sources

bartowski/Qwen_Qwen3-14B-GGUF, Qwen/Qwen3-14B