Meta Llama 3.2 Vision
Last Updated on: Sep 12, 2025
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What is Meta Llama 3.2 Vision?
Llama 3.2 Vision is Meta’s first open-source multimodal Llama model series, released on September 25, 2024. Available in 11 B and 90 B parameter sizes, it merges advanced image understanding with a massive 128 K‑token text context. Optimized for vision reasoning, captioning, document QA, and visual math tasks, it outperforms many closed-source multimodal models.
Who can use Meta Llama 3.2 Vision & how?
- Developers & Engineers: Build multimodal apps like visual assistants, document parsers, and image Q&A tools.
- Analysts & Researchers: Automate chart analysis, document image understanding, and multimodal content summarization.
- Educators & Students: Solve visual math problems, analyze diagrams, and work with text-image inputs in education.
- Enterprises & Teams: Deploy large-context QA systems, OCR pipelines, and image-based chat assistants via API/cloud.
- Open-Source & Edge Advocates: Innovate on a transparent multimodal foundation model with expansive support.
How to Use Llama 3.2 Vision?
- Select Model Size: Choose 11B or 90B based on your compute and accuracy needs.
- Deploy via Platforms: Available on Hugging Face, Oracle OCI, AWS Bedrock, Databricks, Vertex AI, Ollama, and local setups.
- Submit Image+Text: Send mixed prompts—images plus text—within 128K-token context for reasoning or captioning.
- Perform Vision Tasks: Handle image captioning, visual QA (VQAv2), chart or diagram interpretation (ChartQA, DocVQA), and photoreal understanding.
- Optimize Inference: Use grouped-query attention (GQA), quantization, and efficient pipelines—edge variants available for low-latency use.
What's so unique or special about Meta Llama 3.2 Vision?
- Vision Excellence: Achieves top-tier scores—DocVQA
70.7% and AI2 Diagram75.3% (11B) or90.1% &92.3% (90B). - Visual Math & Charts: ChartQA
85.5% and MathVista57.3% with chain-of-thought reasoning. - Massive Context Window: 128K tokens for long-form, multimodal workflows.
- Open-Source Availability: Licensed under Meta’s Community License; commercial-friendly with some usage restrictions.
- Wide Platform Reach: Available across major cloud & local platforms—accessible to developers everywhere.
Things We Like
- Outstanding vision reasoning benchmarks in open-source models
- Large context supports document and image workflows
- Multimodal in a single pipeline—no separate vision endpoint
- Available on multiple platforms, from cloud to edge
- Efficient inference via GQA and quantization options
Things We Don't Like
- Vision focused—doesn’t support audio or video modalities
- In-context window, though large, may still limit ultra-long docs
- 90 B variant requires heavier compute resources
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FAQs
11 B and 90 B parameter variants with vision capabilities.
DocVQA (70–90%), AI2 Diagram (75–92%), ChartQA (85.5%), MathVista (57.3%)—outperforming many models.
Yes—supports mixed prompts up to 128 K tokens.
Available via Hugging Face, Oracle OCI, AWS Bedrock, Databricks, Vertex AI, ollama, and local deployment.
Yes—released under Meta’s Community License; usage restrictions apply for large-scale commercial deployment.
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