Granite 4.0 3B Vision: Compact Multimodal Intelligence for Enterprise Documents

Granite 4.0 3B Vision: Compact Multimodal Intelligence for Enterprise Documents

Hugging Face Blog 7 min read

About this article

A Blog post by IBM Granite on Hugging Face

Back to Articles Granite 4.0 3B Vision: Compact Multimodal Intelligence for Enterprise Documents Enterprise Article Published March 31, 2026 Upvote 6 Madison Lee kristunlee Follow ibm-granite Rogerio Feris rferis Follow ibm-granite Eli Schwartz elischwartz Follow ibm-granite Dhiraj Joshi dhirajjoshi116 Follow ibm-granite Pengyuan Li pengyuan Follow ibm-granite Isaac Sanchez sanchy-ibm Follow ibm-granite Today we're excited to announce Granite 4.0 3B Vision, a compact vision-language model (VLM) designed for enterprise document understanding. It’s purpose-built for reliable information extraction from complex documents, forms, and structured visuals. Granite 4.0 3B Vision excels on the following capabilities: Table Extraction: Accurately parsing complex table structures (e.g., multi-row, multi-column, etc.) from document images Chart Understanding: Converting charts and figures into structured machine-readable formats, summaries, or executable code Semantic Key-Value Pair (KVP) Extraction: Identifying and grounding semantically meaningful key-value field pairs across diverse document layouts The model ships as a LoRA adapter on top of Granite 4.0 Micro, our dense language model, keeping vision and language modular for text-only fallbacks and seamless integration into mixed pipelines. It continues to support vision-language tasks such as producing detailed natural-language descriptions from images (e.g., “Describe this image in detail”). The model can be used standalone or i...

Originally published on March 31, 2026. Curated by AI News.

Related Articles

Llms

My AI spent last night modifying its own codebase

I've been working on a local AI system called Apis that runs completely offline through Ollama. During a background run, Apis identified ...

Reddit - Artificial Intelligence · 1 min ·
Llms

Depth-first pruning seems to transfer from GPT-2 to Llama (unexpectedly well)

TL;DR: Removing the right transformer layers (instead of shrinking all layers) gives smaller, faster models with minimal quality loss — a...

Reddit - Artificial Intelligence · 1 min ·
[2603.16430] EngGPT2: Sovereign, Efficient and Open Intelligence
Llms

[2603.16430] EngGPT2: Sovereign, Efficient and Open Intelligence

Abstract page for arXiv paper 2603.16430: EngGPT2: Sovereign, Efficient and Open Intelligence

arXiv - AI · 4 min ·
[2512.12812] Does Tone Change the Answer? Evaluating Prompt Politeness Effects on Modern LLMs: GPT, Gemini, and LLaMA
Llms

[2512.12812] Does Tone Change the Answer? Evaluating Prompt Politeness Effects on Modern LLMs: GPT, Gemini, and LLaMA

Abstract page for arXiv paper 2512.12812: Does Tone Change the Answer? Evaluating Prompt Politeness Effects on Modern LLMs: GPT, Gemini, ...

arXiv - AI · 4 min ·
More in Open Source Ai: This Week Guide Trending

No comments

No comments yet. Be the first to comment!

Stay updated with AI News

Get the latest news, tools, and insights delivered to your inbox.

Daily or weekly digest • Unsubscribe anytime