Llama 3.2 11B Vision Instruct
VerifiedMeta's open multimodal model for vision-language instruction tasks.
About Llama 3.2 11B Vision Instruct
The model extends the Llama architecture to handle combined text and image inputs. It processes visual data alongside text within its extensive context window. This design enables coherent responses that reference both modalities directly.
Strengths include open-weight availability for customization and strong performance on multimodal instructions. It suits applications such as visual question answering, image description, and document analysis. Developers commonly deploy it for research and production systems requiring integrated vision and language capabilities.
Capabilities
How Llama 3.2 11B Vision Instruct compares
Llama 3.2 11B Vision Instruct (striped bar) vs other multimodal on intelligence, speed and price.
Price
USD per 1M output tokens · Lower is better · Llama 3.2 11B Vision Instruct ranks #19 of 155
Sources: Artificial Analysis (intelligence, speed) · OpenRouter (price).
Best for
Visual Question Answering
The model excels at interpreting images paired with text queries to deliver accurate answers, drawing on its multimodal reasoning and vision understanding capabilities.
Long-Context Image Analysis
It handles extended documents or conversations that combine text and visuals, using its 131072-token context window for detailed image description and analysis.
Instruction-Guided Vision Tasks
Users can provide complex instructions involving images, where the model follows directives for tasks like visual reasoning or generating structured outputs from visual inputs.
Strengths & limitations
Strengths
- +Effective text-image integration
- +Supports extended context windows
- +Solid instruction adherence
- +Efficient for its parameter size
Limitations
- –Smaller scale limits complex reasoning depth
- –Vision performance trails larger multimodal models
- –Can produce visual hallucinations
Cost calculator
Estimate what Llama 3.2 11B Vision Instruct would cost for your usage.
Based on Llama 3.2 11B Vision Instruct's $0.34/1M input · $0.34/1M output. Estimate only — actual cost varies by provider and caching.
Quick start
OpenRouter's API is OpenAI-compatible — most SDKs work by just swapping the base URL. Only the model slug changes between models.
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://openrouter.ai/api/v1",
apiKey: process.env.OPENROUTER_API_KEY,
});
const completion = await client.chat.completions.create({
model: "meta-llama/llama-3.2-11b-vision-instruct",
messages: [{ role: "user", content: "Hello!" }],
});
console.log(completion.choices[0].message.content);Model slug: meta-llama/llama-3.2-11b-vision-instruct
Editor's verdict
Llama 3.2 11B Vision Instruct is Meta's open-weight multimodal with a 131K-token context window.
At $0.34 per 1M output tokens, it is very cost-efficient for its class.
As an open-weight model you can self-host it or call it through a hosted API.
Best suited to effective text-image integration and supports extended context windows.
Frequently asked questions
The model supports a context length of 131072 tokens, enabling long-context text processing alongside visual inputs.
User reviews
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