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Available now on ModelsLab · Language Model

Meta Llama 3.2 11B Vision Instruct TurboVision LLM Turbo Speed

Try Meta Llama 3.2 11B Vision Instruct TurboAPI Documentation

Process Images Text Fast

Multimodal Core

Image Text Reasoning

Handles image captioning, visual QA, retrieval with 11B parameters and 128K context.

Turbo Optimized

Production Speed Balance

Delivers high accuracy at low cost for scalable enterprise multimodal tasks.

Vision Adapter

1120x1120 Resolution

Supports high-res images via cross-attention on Llama 3.1 base.

Examples

See what Meta Llama 3.2 11B Vision Instruct Turbo can create

Copy any prompt below and try it yourself in the playground.

Chart Analysis

“Analyze this sales chart image. Extract key trends, quarterly growth rates, and predict next quarter based on patterns. Output in JSON.”

Document OCR

“Read this invoice image. Extract vendor name, date, total amount, line items. Format as structured list.”

Diagram Explain

“Describe this network architecture diagram. Identify components, connections, and suggest improvements for scalability.”

Product Catalog

“Caption these product photos. Generate descriptions highlighting features, materials, dimensions for e-commerce listing.”

For Developers

A few lines of code.
Vision instruct. One call.

ModelsLab handles the infrastructure: fast inference, auto-scaling, and a developer-friendly API. No GPU management needed.

  • Serverless: scales to zero, scales to millions
  • Pay per token, no minimums
  • Python and JavaScript SDKs, plus REST API
API Documentation 
import requests


response = requests.post(
    "https://modelslab.com/api/v7/llm/chat/completions",
    json={
  "key": "YOUR_API_KEY",
  "prompt": "",
  "model_id": ""
}
)
print(response.json())

FAQ

Common questions about Meta Llama 3.2 11B Vision Instruct Turbo

Read the docs

Ready to create?

Start generating with Meta Llama 3.2 11B Vision Instruct Turbo on ModelsLab.

Try Meta Llama 3.2 11B Vision Instruct TurboAPI Documentation