Granite 4.1

Overview

IBM's Granite 4.1 in its generic 3B Ollama tag — Apache 2.0, 128k context, robust tool calling, and a sub-2GB Q4 footprint. Code- and chat-oriented.

When to pick this model

• Agent and tool-use pipelines where license clarity matters
• Enterprise deployments that require fully permissive Apache 2.0 weights
• Multilingual chat across the 12 languages IBM trained on
• Lightweight coding assistants on developer machines

VRAM requirements by quantization

Quantization	VRAM required
Q4_K_M (recommended)	1.7 GB
Q5_K_M	2.1 GB
Q8_0	3.2 GB
FP16 (no quantization)	6 GB

VRAM figures include model weights plus a typical 8k KV cache and ~600 MB runtime overhead (Ollama / llama.cpp baseline). Add headroom for higher context lengths.

Strengths

• Fully Apache 2.0 — no click-through, no commercial caveats
• 128k context window
• OpenAI-compatible tool calling that works reliably
• Compact ~1.7GB VRAM at Q4

Limitations

• Hugging Face distribution is gated even though the license is open
• Generic Ollama tag doesn't pin a specific size variant

Architecture & training

Architecture: Dense transformer · 3B parameters · 128k context

Training: IBM's Granite 4.1 family. Multilingual training (12 languages), OpenAI-compatible tool calling.

Quick start

ollama run granite4.1

Or use the open-source MCP server to query this model from Claude Desktop, Cursor, or any MCP-compatible client.