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Granite 4.1 VRAM Requirements - IBM 3B, 8B, and 30B Hardware Guide

Exact practical VRAM estimates for IBM Granite 4.1 3B, 8B, and 30B at Q4, Q5, Q8, FP8, and BF16. Includes RTX, Apple Silicon, long-context, and enterprise RAG guidance.

IBM Granite 4.1 is a clean fit for Will It Run AI users: small enough for consumer GPUs, permissive enough for production, and long-context enough for RAG and agent workflows.

IBM's release covers dense 3B, 8B, and 30B language models trained on roughly 15T tokens, with supervised fine-tuning, GRPO/DAPO reinforcement learning, and context extension up to 512K tokens. The official technical walkthrough is here: Granite 4.1 LLMs: How They're Built.

Quick VRAM Table

These are practical weight-size estimates. Add KV cache and runtime overhead, especially if you use the 512K context window.

ModelQ4 / 4-bitQ5Q8FP8BF16
Granite 4.1 3B~2 GB~2.4 GB~3.5 GB~3.2 GB~6 GB
Granite 4.1 8B~5 GB~6 GB~9 GB~8.5 GB~16 GB
Granite 4.1 30B~18 GB~22 GB~34 GB~31 GB~60 GB

The 8B model is the sweet spot for 8-12 GB GPUs. The 30B model is the serious local workstation target.

What Hardware Runs Granite 4.1?

8 GB GPUs

An RTX 4060 8GB, RTX 3070 8GB, or Arc B580 12GB class card should run:

  • Granite 4.1 3B at Q8 or BF16
  • Granite 4.1 8B at Q4 with useful context
  • Granite 4.1 30B only with CPU offload, not recommended

For a direct 8GB comparison, use the VRAM calculator or compare against best AI models for 8GB VRAM.

12-16 GB GPUs

This is where Granite 4.1 8B becomes comfortable. You can use Q8 or FP8 with room for long prompts, retrieval chunks, and multi-turn chat.

Granite 4.1 30B still needs Q3/Q4 plus aggressive context limits on 16 GB. If you want a 30B-class model on a 16GB card, Qwen3.6-27B at Q4 is usually the better target; see Qwen3.6-27B VRAM Requirements.

24 GB GPUs

An RTX 4090, RTX 3090, RTX 6000 Ada 24GB, or Radeon RX 7900 XTX can run Granite 4.1 30B at Q4.

Recommended setup:

  • Granite 4.1 30B Q4_K_M for general assistant, RAG, and coding
  • Granite 4.1 8B Q8 if latency matters more than raw quality
  • Keep context moderate unless you have 32 GB+ VRAM or unified memory

For a broad hardware comparison, see what you can run on 16GB, 24GB, and 32GB VRAM.

Apple Silicon

Apple Silicon is a strong Granite 4.1 target because unified memory lets the model and KV cache share the same pool.

MacBest Granite 4.1 target
16 GB MacGranite 4.1 8B Q4/Q5
24 GB MacGranite 4.1 8B Q8 or 30B Q4 with limited context
48-64 GB MacGranite 4.1 30B Q5/Q8
96-128 GB MacGranite 4.1 30B BF16 or very long context

If you are choosing a Mac specifically for local LLMs, start with MacBook Air M4 vs Pro M4 for local LLMs.

Long Context Changes the Math

Granite 4.1's 512K context headline is useful, but KV cache can become larger than the quantized model weights. A 30B model at Q4 may fit in 24 GB at normal context, then fail when pushed into hundreds of thousands of tokens.

Practical guidance:

  • 8B at 32K-128K context is realistic on 16-24 GB hardware.
  • 30B at 32K context is realistic on 24 GB.
  • 30B at 128K+ context wants 48 GB+.
  • 30B near 512K context is a workstation/server workload.

Granite 4.1 vs Qwen, Gemma, and DeepSeek

Granite 4.1 is not just a benchmark-chasing release. The appeal is enterprise practicality: Apache 2.0, predictable dense architecture, strong RAG/coding positioning, and a model family that scales from 3B to 30B.

PickBest when
Granite 4.1 8BYou want Apache 2.0, fast RAG, and 8-16 GB hardware
Granite 4.1 30BYou want a dense 30B enterprise assistant on 24 GB+
Qwen3.6-27BYou want the strongest local coding model in a consumer footprint
Gemma 4 26B-A4BYou want MoE speed and Apache 2.0 reasoning quality
DeepSeek-V4You need million-token reasoning and can afford workstation memory

Recommendation

Add Granite 4.1 to your shortlist if you care about commercial use, RAG, code assistance, and operational simplicity.

For most local users:

  • 8 GB VRAM: Granite 4.1 8B Q4
  • 16 GB VRAM: Granite 4.1 8B Q8
  • 24 GB VRAM: Granite 4.1 30B Q4
  • 48 GB+ VRAM or Mac unified memory: Granite 4.1 30B Q8 or long-context workloads

Use the Will It Run AI calculator to compare Granite 4.1 against Qwen, Gemma, DeepSeek, and your exact GPU or Mac.

Frequently Asked Questions

How much VRAM does Granite 4.1 need?

Granite 4.1 3B needs about 2 GB at Q4, 4 GB at Q8, and 6 GB at BF16. Granite 4.1 8B needs about 5 GB at Q4, 9 GB at Q8, and 16 GB at BF16. Granite 4.1 30B needs about 18 GB at Q4, 34 GB at Q8, and 60 GB at BF16 before KV cache.

Can I run Granite 4.1 30B on an RTX 4090?

Yes at Q4 or FP8 with moderate context. Granite 4.1 30B Q4 leaves several GB for KV cache on a 24 GB RTX 4090. Q8 does not fit on a single 24 GB GPU.

Is Granite 4.1 open for commercial use?

Yes. IBM released the Granite 4.1 language models under Apache 2.0, which makes them attractive for commercial RAG, coding, and assistant deployments.

What makes Granite 4.1 different from Granite 4.0?

Granite 4.1 moves back to dense 3B, 8B, and 30B decoder-only models with strong data curation and up to 512K context. IBM reports the 8B instruct model matching or beating the previous Granite 4.0-H-Small 32B-A9B MoE in several comparisons.