Llama 3.2 11B Vision is a multimodal model with 11 billion parameters, designed to handle tasks combining visual and textual data. It excels in tasks such as image captioning and visual question answering, bridging the gap between language generation and visual reasoning. Pre-trained on a massive dataset of image-text pairs, it performs well in complex, high-accuracy image analysis. Its ability to integrate visual understanding with language processing makes it an ideal solution for industries requiring comprehensive visual-linguistic AI applications, such as content creation, AI-driven customer service, and research. Click here for the [original model card](https://github.com/meta-llama/llama-models/blob/main/models/llama3_2/MODEL_CARD_VISION.md). Usage of this model is subject to [Meta's Acceptable Use Policy](https://www.llama.com/llama3/use-policy/).

Try Meta: Llama 3.2 11B Vision Instruct

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One-Click Config

Optimized configs for your favorite AI tools.

Claude Code

# Claude Code works via OpenRouter's Anthropic-compatible API.
# Note: Only paid Anthropic Claude models are supported (e.g. claude-sonnet-4.6, claude-opus-4).
# Browse available Claude models at: https://openrouter.ai/models?q=anthropic

# Add to ~/.zshrc or ~/.bashrc
export OPENROUTER_API_KEY="<your-openrouter-api-key>"  # Get at https://openrouter.ai/settings/keys
export ANTHROPIC_BASE_URL="https://openrouter.ai/api"
export ANTHROPIC_AUTH_TOKEN="$OPENROUTER_API_KEY"
export ANTHROPIC_API_KEY=""  # Must be explicitly empty to avoid conflicts

# Optional: pin specific models for each role
# export ANTHROPIC_DEFAULT_SONNET_MODEL="anthropic/claude-sonnet-4.6"
# export ANTHROPIC_DEFAULT_HAIKU_MODEL="anthropic/claude-haiku-4.5"

# Then simply run: claude

Cursor

# Cursor → Settings (⚙️) → Models → Add Model
# Enter the model name exactly as shown, then fill in:
#   Override OpenAI Base URL: https://openrouter.ai/api/v1
#   OpenAI API Key: <your-api-key>   # Get at https://openrouter.ai/workspaces/default/keys
# Click "Verify" to confirm the connection, then enable the model.
#
# Model name to add: Meta: Llama 3.2 11B Vision Instruct

Codex

# Add to ~/.zshrc or ~/.bashrc
export OPENAI_BASE_URL="https://openrouter.ai/api/v1"
export OPENAI_API_KEY="<your-api-key>"  # Get at https://openrouter.ai/workspaces/default/keys

# Then run:
codex --model "Meta: Llama 3.2 11B Vision Instruct"

Gemini CLI

# ~/.gemini/settings.json
{
  "apiKey": "<your-api-key>",
  "model": "Meta: Llama 3.2 11B Vision Instruct"
}
# Get API key at https://openrouter.ai/workspaces/default/keys

OpenCode

// ~/.config/opencode/opencode.json
{
  "$schema": "https://opencode.ai/config.json",
  "provider": {
    "free-llm": {
      "npm": "@ai-sdk/openai-compatible",
      "name": "Free LLM",
      "options": {
        "baseURL": "https://openrouter.ai/api/v1",
        "apiKey": "<your-api-key>"
      },
      "models": {
        "Meta: Llama 3.2 11B Vision Instruct": { "name": "Meta: Llama 3.2 11B Vision Instruct" }
      }
    }
  }
}
// Get API key at https://openrouter.ai/workspaces/default/keys

Hermes

# Step 1 — Edit config.yaml
# Windows: C:\Users\<you>\AppData\Local\hermes\config.yaml
# macOS/Linux: ~/.config/hermes/config.yaml

model:
  default: Meta: Llama 3.2 11B Vision Instruct
  provider: custom
  base_url: ${CUSTOM_BASE_URL}
  api_key: ${CUSTOM_API_KEY}
  model_aliases:
    Meta: Llama 3.2 11B Vision Instruct:
      model: "Meta: Llama 3.2 11B Vision Instruct"
      provider: "custom"

# Step 2 — Edit .env (same directory as config.yaml)
# Windows: C:\Users\<you>\AppData\Local\hermes\.env
# macOS/Linux: ~/.config/hermes/.env

# ========================
# Custom API (OpenAI-compatible)
# ========================
CUSTOM_API_KEY=<your-api-key>        # Get at https://openrouter.ai/workspaces/default/keys
CUSTOM_BASE_URL=https://openrouter.ai/api/v1

OpenClaw

// ~/.openclaw/openclaw.json  (JSON5 format)
{
  "agents": {
    "defaults": {
      "model": {
        "primary": "Meta: Llama 3.2 11B Vision Instruct",
      },
    },
  },
  "models": {
    "providers": {
      // Option A — Built-in provider (OpenAI, Anthropic, Google…)
      // Just add apiKey; OpenClaw handles the baseUrl automatically
      // "openai": { "apiKey": "<your-api-key>" },

      // Option B — Custom OpenAI-compatible base URL (e.g. OpenRouter, NVIDIA)
      "free-llm": {
        "baseUrl": "https://openrouter.ai/api/v1",
        "apiKey": "<your-api-key>",  // Get at https://openrouter.ai/workspaces/default/keys
        "api": "openai-completions", // openai-completions | anthropic-messages | …
        "models": [
          { "id": "Meta: Llama 3.2 11B Vision Instruct", "name": "Meta: Llama 3.2 11B Vision Instruct" },
        ],
      },
    },
  },
}
// Apply: openclaw gateway restart
// Verify: openclaw doctor --fix

FAQ

Is it really free?

No, Meta: Llama 3.2 11B Vision Instruct was previously free but has since transitioned to a paid model. Browse our free model directory for alternatives.

How to use it with Cursor?

Go to Cursor Settings > Models, add a custom model named "Meta: Llama 3.2 11B Vision Instruct", and set the Base URL to "https://openrouter.ai/api/v1".

OpenRouter: Meta: Llama 3.2 11B Vision Instruct