Granite 4.1 30B — VRAM, Speed & Local Setup

Autor: Jakub Rusinowski · Ostatnia aktualizacja: 29 kwietnia 2026

Model libraryIBM Granite 4.1 → Granite 4.1 30B

Largest Granite 4.1 tier — a hybrid Mamba2/attention design (interleaved SSM + attention layers), not MoE despite the 4.0 generation using MoE. ~18GB at FP8 (Q4 likely lower, ~12-15GB, unconfirmed). Context extendable to 512K. Apache 2.0.

Granite 4.1 30B needs about 19 GB of VRAM at FP8 (Q4 est. ~12-15GB, unconfirmed) — quantized weights plus framework overhead, before any KV cache. On Apple Silicon that figure comes out of unified memory.

Specifications

Parameters30 Billion
Context window128,000
ArchitectureHybrid Mamba2 + Attention (SSM)
ProviderIBM
LicenceApache 2.0
Specified atFP8 (Q4 est. ~12-15GB, unconfirmed)
System RAM32 GB
Record updated2026-04-29

Licence

Apache-2.0commercial use permitted. Commercial use permitted. No usage restrictions beyond attribution.

VRAM and Speed by Quantization

Modelled on a reference NVIDIA RTX 4090 (24 GB). Weights plus framework overhead only — this model publishes no architecture we can read, so no KV cache is included. A real session needs more; the figure is a floor, not a target. Speed figures are ESTIMATES from the memory-bandwidth roofline described on the methodology page, not benchmarks we ran — rows marked measured come from published or reader-submitted runs. VRAM here includes the KV cache, so it reads higher than the headline figure above, which does not.

QuantBits/weightWeightsVRAM neededEst. speedFit on 24 GB
Q2_K2.639.9 GB10.7 GB~61 tok/s (est.)Fits comfortably
Q3_K_M3.4112.8 GB13.6 GB~49 tok/s (est.)Fits comfortably
Q4_K_M4.8318.1 GB18.9 GB~37 tok/s (est.)Fits comfortably
Q5_K_M5.6721.3 GB22.1 GB~32 tok/s (est.)Tight fit
Q6_K6.5624.6 GB25.4 GB~4 tok/s (est.)Offloads to system RAM (slow)
Q8_08.5031.9 GB32.7 GB~3 tok/s (est.)Offloads to system RAM (slow)
F1616.0060 GB60.8 GBWon't fit

Want to set your own context length and KV-cache quantization? Use the interactive VRAM calculator.

Buy This HardwareAMD Radeon RX 7900 XT 20GB — 20 GB VRAM · 315 W board powerDeploy in the Cloud NowRTX 4090 on RunPod — from $0.34/hr · rate checked 2026-07

or compare on Vast.ai from $0.35/hr (typical low · varies)

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Recommended GPU

The cheapest catalogued GPU that runs Granite 4.1 30B is the AMD Radeon RX 7900 XT (20 GB).

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AMD Radeon RX 7900 XT 20GB
20 GB VRAM · 315 W board power
Ceny w 2026 są niestabilne — sprawdź aktualną ofertę.
Sprawdź cenę na Amazon

How to Run Granite 4.1 30B

Install Ollama, then run:

ollama run granite4.1:30b

Weights on Hugging Face: ibm-granite/granite-4.1-30b.

Best for: enterprise, long context, reasoning, mid range gpu.

Can I Run Granite 4.1 30B on My GPU?

Other IBM Granite 4.1 Sizes

Granite 4.1 30B — Frequently Asked Questions

How much VRAM does Granite 4.1 30B need?
About 19 GB at FP8 (Q4 est. ~12-15GB, unconfirmed) — quantized weights plus framework overhead, before any KV cache. The cache grows with context length and is added on top; the table above folds it in. Apple Silicon counts unified memory toward the same figure.
Does Granite 4.1 30B run on an RTX 4090 (24 GB)?
Yes. Granite 4.1 30B needs about 19 GB at FP8 (Q4 est. ~12-15GB, unconfirmed), inside a 24 GB card, at an estimated 37 tokens/sec.
How do I run Granite 4.1 30B locally?
Install Ollama and run `ollama run granite4.1:30b`. That pulls the weights and starts a local OpenAI-compatible endpoint; after the download nothing leaves the machine.
What other sizes does IBM Granite 4.1 come in?
Granite 4.1 3B (3 GB), Granite 4.1 8B (6 GB), Granite 4.1 30B (19 GB). Every size shares the family's training and licence; the larger ones score higher and need proportionally more memory.

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