Llama 3.2 11B Vision
Llama 3's first vision-language model. Image understanding via a separately-trained ViT adapter bolted onto Llama 3 weights. Useful for OCR-adjacent workloads, document understanding, and image captioning at a permissive licence. The 11B size makes it cheap to host. Combined with the 128K text context, it handles long PDF-with-images workflows comfortably on a single 4090.
- Parameters
- 11B
- Context length
- 128K
- Modality
- text, vision
- Released
- 2024-09-25
Memory & hardware
- VRAM (fp16)
- 22 GB
- VRAM (Q4)
- 6.6 GB
- Recommended
- RTX 4090 24GB (fp16)
- Quantizations
- fp16, q8_0, q5_k_m, q4_k_m
License: Llama 3 Community License
- SPDX
- —
- Commercial use
- Yes
- Modification
- Yes
- Redistribution
- Yes
Benchmarks
Hosted inference pricing
No provider we track publishes a per-token price for this model today. What each one used to offer is listed below.
No longer listed
Providers that used to serve this model. We don't republish their old rates — the dates below are the provider's own.
- groqGroq shut down llama-3.2-11b-vision-preview on 14 April 2025.Source ↗
Run it yourself
Drop-in commands for the three most common open-source inference paths. The Ollama tag is a best-effort match against the registry; verify the size variant before pulling.
ollama run llama3.2:11b
vllm serve meta-llama/Llama-3.2-11B-Vision-Instruct
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("meta-llama/Llama-3.2-11B-Vision-Instruct")
model = AutoModelForCausalLM.from_pretrained(
"meta-llama/Llama-3.2-11B-Vision-Instruct", device_map="auto", torch_dtype="auto"
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