What hardware do you need to run Granite 4.2 8B?

Granite 4.2 8B at Q4_K_M is 5.3 GB of weights, with a context ceiling of 128k tokens. IBM's small model, aimed at enterprises that care about provenance. On the cheapest machine that runs it, a Mac mini M6, 24GB, it generates 12 tok/s at 32k of context, worked out from memory bandwidth.

How good is Granite 4.2 8B, really?

On the Artificial Analysis Intelligence Index v4.3 it scores 12, 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.

Head to head with its neighbours on the leaderboard: vs Ling 3.0 tiny above it, vs GLM-4.5-Air below. One more model needs much the same memory at 32k of context: vs Qwen3 8B.

What Granite 4.2 8B costs either way

Renting the same model costs $0.06 per million input tokens and $0.15 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 8B

Every machine here runs it, but not to the same length. The Mac mini M6, 24GB stops at 32k; the AMD Radeon AI PRO R9700, 32GB 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: 51 of the 56 machines on this site hold it at 32k. Within a family only memory decides, so that is every Mac Studio, Strix Halo box and NVIDIA card at any size, 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 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. 1 of the 7 above reaches it, and the slowest is 11 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, this one among them.

It fits in less memory than that: the smallest size here that runs it at 32k is 12 GB, on the GeForce RTX 3060, 12GB at $329, card only, which hands a model 11 GB and is no longer sold.

Run Granite 4.2 8B at 128k on the AMD Radeon AI PRO R9700, 32GB

How much memory does Granite 4.2 8B need at 128k?

Every figure above is priced at 32k of context. At 128k, this model's own ceiling, Granite 4.2 8B needs 26.8 GB rather than 10.7 GB. The weights are the same either way; the key-value cache goes from 5.4 GB to 21.5 GB.

33 of the 37 machines here still sold at a published price hold Granite 4.2 8B at 32k and 27 hold it at 128k. The cheapest still sold goes from the Mac mini M6, 24GB at $1,099 to the Radeon AI PRO R9700, 32GB at $1,299, card only. 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 Radeon AI PRO R9700, 32GB it runs 52 tok/s estimated at 32k and 21 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 8B needs 11 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

8B

Quantisation

Q4_K_M

Weights on disk

5.3 GB

KV cache

5.4 GB at 32k context — Plain grouped-query attention on all 40 layers, so the context costs real memory. head_dim is absent from the config and derived as hidden_size ÷ heads. How weights and cache add up.

Maximum context

128k tokens

Licence

Apache 2.0

Sources

ibm-granite/granite-4.2-8b