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Llama 3.2 90B Vision Instruct

Llama 3.2 90B Vision Instruct is Meta's multimodal 90B checkpoint with image and text input, text output and a 128K context window.

Multimodal Language ModelTextImage Free
In plain English

What is this model and why does it matter?

Llama 3.2 90B Vision Instruct is Meta's multimodal 90B model for image understanding and text generation with a 128K context window.

Image understandingDocument and chart analysisVisual question answeringMultimodal RAGResearch
Model overview

Llama 3.2 90B Vision Instruct: features, use cases and important details

Llama 3.2 90B Vision Instruct is Meta’s 90B multimodal instruction model from the Llama 3.2 release.

Verified model facts

Meta documents text and image input, text output, a 128K context window, a December 2023 data cutoff and a September 25, 2024 release.

Best fit

It is built for visual question answering, chart and document understanding, image-aware assistants and multimodal RAG.

Limitations

It can misinterpret visual content, image+text usage is officially English-focused, and the model requires substantial serving hardware.

Get started

How to use this model

  1. Accept the Llama 3.2 Community License.
  2. Download the official vision checkpoint.
  3. Provision suitable GPU infrastructure.
  4. Provide image and text inputs using the documented format.
  5. Evaluate visual reasoning and safety on representative data.
Copy and try

Example prompts

  • Explain the key trend in this chart.
  • Read this screenshot and summarize the important fields.
  • Compare this image with the written requirements.
Capabilities

What it can do

  • Image understanding
  • 128K context
  • Visual reasoning
  • Text generation
  • Multilingual text-only tasks
Best for

Practical use cases

  • Visual Q&A
  • Chart analysis
  • Document understanding
  • Multimodal assistants
Pricing

What does it cost?

Open-weight Meta checkpoint; no direct Meta per-token price applies to the downloadable model.

Simple summarySelf-hosting the 90B multimodal model requires substantial GPU memory; costs depend on infrastructure.

What stands out

  • Official Meta multimodal weights
  • 128K context
  • Strong image understanding for its generation

Things to consider

  • 90B model has significant hardware requirements
  • Image+text support is officially English-focused
  • Custom license
Limitations

Important restrictions and trade-offs

  • Can misread images or charts
  • Static December 2023 cutoff
  • Not a direct Meta hosted API
SimplifyAITools verdict

Our editorial take

A verified multimodal Llama checkpoint for self-hosted visual understanding; choose 11B for lower infrastructure needs and 90B when quality justifies the serving cost.

References

Primary sources

  1. Open source 1 ↗
  2. Open source 2 ↗
  3. Open source 3 ↗
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