What hardware do you need to run Granite 4.2 30B?

Granite 4.2 30B at Q4_K_M is 18 GB of weights, with a context ceiling of 128k tokens. Dense 30B; the context costs far more memory than the hybrid models of the same size. On the cheapest machine that runs it, a Radeon AI PRO R9700, 32GB, it generates 21 tok/s at 32k of context, worked out from memory bandwidth.

How good is Granite 4.2 30B, really?

On the Artificial Analysis Intelligence Index v4.3 it scores 15, which puts it in the Haiku-class band. In the same band as Anthropic's cheap, fast tier. Every current OpenAI model scores above this band. See the whole table.

Head to head with its neighbours on the leaderboard: vs Gemma 4 31B it above it, vs GLM-4.7-Flash below. One more model needs much the same memory at 32k of context: vs Nemotron 3.5 Lightning 30B-A3B.

What Granite 4.2 30B costs either way

Nobody rents Granite 4.2 30B by the token. The closest hosted match, GLM-4.7-Flash, costs $0.0605 per million input tokens and $0.4 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 Granite 4.2 30B

Every machine here runs it, but not to the same length. The AMD Radeon AI PRO R9700, 32GB stops at 32k; the DGX Spark GB10 Grace Blackwell, 128GB takes it to 128k, this model's own ceiling. The weights are the same size on every machine; what differs is the memory left for the key-value cache, which grows with every token you keep.

The table is the cheapest machine in each family, not the only one that runs it: 38 of the 56 machines on this site hold it at 32k. Within a family only memory decides, so that is every Mac Studio at any size, every NVIDIA card with 32GB or more, every Mac mini and MacBook Pro with 48GB or more, every Strix Halo box with 64GB 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 128k 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. Nothing above reaches it, and the quickest is 47 tok/s.

The cheapest machine that runs it is sold with 32 GB. There is a page on what 32 GB runs, machine by machine: it names the 6 machines here sold at that size, and the 32 current models the roomiest of them holds at 32k, this one among them.

Run Granite 4.2 30B at 128k on the DGX Spark GB10 Grace Blackwell, 128GB

How much memory does Granite 4.2 30B need at 128k?

Every figure above is priced at 32k of context. At 128k, this model's own ceiling, Granite 4.2 30B needs 52.1 GB rather than 26.3 GB. The weights are the same either way; the key-value cache goes from 8.6 GB to 34.4 GB.

27 of the 37 machines here still sold at a published price hold Granite 4.2 30B at 32k and 13 hold it at 128k. The cheapest still sold goes from the Radeon AI PRO R9700, 32GB at $1,299, card only to the Framework Desktop, 128GB at $3,449. The Radeon AI PRO R9700, 32GB is priced as the card alone, so add the PC around it before comparing it with a complete computer.

On the Framework Desktop, 128GB it runs 7.3 tok/s estimated at 32k and 3.7 tok/s estimated at 128k. Every token generated reads the whole cache back, so a longer window is slower as well as bigger.

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 Granite 4.2 30B needs 26 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 Framework Desktop, 32GB at $1,269. The table above starts at $1,299, card only.

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

29.3B

Quantisation

Q4_K_M

Weights on disk

18 GB

KV cache

8.6 GB at 32k context — Plain grouped-query attention on all 64 layers, so long contexts are expensive here. head_dim derived from hidden_size ÷ heads. How weights and cache add up.

Maximum context

128k tokens

Licence

Apache 2.0

Sources

ibm-granite/granite-4.2-30b