Using Llama 3.2 11B Vision Instruct on Vercel AI Gateway
Implementation guide · Llama 3.2 · AI at Meta
ServerlessOpen Weights
Vercel AI Gateway exposes Llama 3.2 11B Vision Instruct through model ID meta/llama-3.2-11b. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.
Last refreshed 2026-07-09. Next refresh: weekly.
Quick Start
- 1
- 2Use the Vercel AI Gateway SDK or REST API to call
meta/llama-3.2-11b— see the documentation for request format. - 3
Code Examples
Install
pip install openaiAPI key
AI_GATEWAY_API_KEYModel ID
meta/llama-3.2-11bcreator/model-name e.g. kwaipilot/kat-coder-pro-v2
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["AI_GATEWAY_API_KEY"],
base_url="https://ai-gateway.vercel.sh/v1"
)
response = client.chat.completions.create(
model="meta/llama-3.2-11b",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Pricing on Vercel AI Gateway
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.16 |
| Output tokens | $0.16 |
Capabilities
VisionMultimodalStructured Outputs
About Llama 3.2 11B Vision Instruct
Instruction-tuned 11B Llama 3.2 Vision model for image reasoning, visual question answering, document understanding, and captioning. NVIDIA NIM lists text plus image input, text output, and a 128K context window for the Llama 3.2 Vision collection.
Model Specs
Released2024-09-25
Parameters10.6B
Context128k
ArchitectureDecoder Only
Knowledge cutoff2024-03