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
USD per million tokens.
| Provider | Input | Output | |
|---|---|---|---|
| groqCheapest | $0.18 | $0.18 |
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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