Run Granite 4.2 8B locally: hardware requirements
Granite 4.2 8B by IBM installs on a paired computer through idapt's local engine. RAM decides whether a build fits; a GPU only changes speed. Local runs are not billed.
- Download
- 5.0 GB
- RAM needed
- 8.0 GB
- Builds
- 1
Will it run on your machine?
Enter your system RAM to get verdicts. RAM decides whether a build fits; a GPU only changes speed.
Every build
| Build | Quantization | Download | RAM needed |
|---|---|---|---|
| 8bDefault | full precision | 5 GB | 8 GB |
RAM figures are working-set recommendations: when GPU memory is short, the runtime spills to CPU and system memory instead of failing.
Install it
Pair a computer with idapt and install Granite 4.2 8B from the model page: the local engine bootstraps itself, pulls the build you pick, and streams progress. Or pull it directly:
ollama pull granite4.2:8bFrequently asked
How much RAM do I need to run Granite 4.2 8B locally?
The smallest Granite 4.2 8B build runs with about 8 GB of system RAM; the largest needs 8 GB. RAM is the binding requirement: when GPU memory is short, the runtime spills to CPU and system memory instead of failing.
Which quantization of Granite 4.2 8B should I pick?
Start with the default 8b build: a 5 GB download that wants about 8 GB of RAM. Smaller quantizations shrink the download and memory needs at some cost in output quality; larger ones do the reverse.
Do I need a GPU to run Granite 4.2 8B?
No. A GPU with enough VRAM makes generation faster, but Granite 4.2 8B runs on CPU and system RAM alone. Whether a build fits is decided by RAM; the GPU only changes speed.
How big is the Granite 4.2 8B download?
About 5 GB for the single available build.
Can idapt install Granite 4.2 8B for me?
Yes. Pair a computer with idapt and install Granite 4.2 8B from this page: the local engine bootstraps itself, pulls the build you pick (ollama pull granite4.2), and streams download progress. Local runs are not billed.
Part of the Granite 4.2 8B model page · Granite 4.2 8B pricing · Check every local model against your hardware