Llama 3.2 Vision 11B

Overview

Meta's first official multimodal Llama. An 11B vision-language model built on Llama 3.1 8B with added image adapters and a 128k text context.

When to pick this model

• OCR and document understanding on a consumer GPU
• Image captioning and description pipelines
• Chart and graph analysis
• Mixed text-and-image RAG workloads
• Llama ecosystem deployments needing vision

VRAM requirements by quantization

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.

Published benchmark scores

Scores published by the model author or aggregated from public leaderboards. Re-measured monthly by our editorial team.

Strengths

• 128k text context with image input
• Strong OCR and image description
• Built on the well-supported Llama 3 base
• First-party Meta multimodal release

Limitations

• Vision quality trails Qwen2-VL and LLaVA-OneVision
• Subject to Llama Community license terms
• No video understanding
• Image inputs add significant VRAM overhead

Architecture & training

Architecture: Dense · 11B · vision cross-attention · CLIP encoder · Llama 3.2

Training: Llama 3.1 8B + vision adapters. First official Meta vision model.

Quick start

ollama run llama3.2-vision:11b

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