Granite 4.2 30B VRAM requirements

How much VRAM does Granite 4.2 30B need?

Granite 4.2 30B needs 20.8 GB at Q4_K_M, 34.6 GB at Q8_0 and 62.7 GB at FP16 with 8,192 tokens of context and one request. Each total below is the weights plus the FP16 KV cache and the runtime overhead (0.5 GB plus 10%), and each row opens the calculator with that setting. What the GGUF names mean.

Fine-tuning Granite 4.2 30B? Granite 4.2 30B VRAM for LoRA, QLoRA and full training.

Granite 4.2 30B GGUF files on Hugging Face

The 8 GGUF files llama.cpp picks for Granite 4.2 30B with -hf <repo>:<QUANT>, with the bytes the Hugging Face file list reported on 2026-09-29. Each total is that file plus the FP16 KV cache and 0.5 GB + 10%, one request. "vs estimate" compares the file with the bits-per-weight size the table above uses.

GB here is GiB (1024³ bytes), as everywhere on this site; Hugging Face shows the Q4_K_M file as 18.0 GB, in 10⁹ bytes.

Which Granite 4.2 30B GGUF fits a 16, 24, 32, 48 or 80 GB GPU or a Mac

From the file sizes above: the largest file that fits each machine with an 8K context and 0.5 GB left free, the longest context it then has room for, and the longest context for Q4_K_M (16.8 GB). One request, FP16 KV cache.

Run Granite 4.2 30B with llama.cpp or Ollama

llama-server -hf bartowski/granite-4.2-30b-GGUF:Q4_K_M -c 16384

granite-4.2-30b-Q4_K_M.gguf, 18.0 GB, from bartowski/granite-4.2-30b-GGUF (checked 2026-09-29). On a 24 GB RTX 3090 / 4090, Q4_K_M with -c 16384 takes 23.4 GB and leaves 647 MB. The file is 301 MB over the Q4_K_M estimate, so -c counts the file.

ollama run granite4.2:30b

Ollama library tag granite4.2:30b; its quant is Ollama's choice. Same context: /set parameter num_ctx 16384.

Granite 4.2 30B at 8K, 32K and 128K (full) tokens of context

All 64 layers use full attention. Each extra token of context adds 256 KB of FP16 cache per request. The last column is the smallest setup here, one card or a group, that holds it at Q4_K_M. How the KV cache works.

How fast Granite 4.2 30B writes

Tokens per second for one request with 8,192 tokens of context, estimated from memory bandwidth. A dash means it does not fit on one card. Try other settings in the speed calculator.

Longest context on one GPU

How many tokens of context Granite 4.2 30B fits on a single card with one request, an FP16 KV cache and 0.5 GB left free. "Full" means the model's whole context window fits.

Model details

Parameters

29.3B (29,276,770,304)

Layers

All 64 layers use full attention

Attention cache

8 KV heads × 128

Context length

131,072 tokens

Published weights

54.5 GB (BF16)

On Hugging Face

ibm-granite/granite-4.2-30b

Granite 4.2 30B next to similar-sized models

The three models here closest to it in parameter count, at Q4_K_M with 8,192 tokens of context.