OSAIM
Open Source AI Models

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

MMLU
73.0
Benchmarks last verified 2026-05-18.

Hosted inference pricing

USD per million tokens.

ProviderInputOutput
groqCheapest$0.18$0.18
Pricing last verified 2026-05-18. Providers update rates frequently; confirm before integrating.

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.

Run Llama 3.2 11B Vision locally
Ollama (easiest)
ollama run llama3.2:11b
Single-line install + run; uses the official Ollama registry tag for this family.
vLLM (production)
vllm serve meta-llama/Llama-3.2-11B-Vision-Instruct
High-throughput hosted inference; one command to expose an OpenAI-compatible HTTP server.
Transformers (Python)
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"
)
Direct PyTorch usage. Pin a torch / cuda version that matches your GPU.
Hugging Face ID: meta-llama/Llama-3.2-11B-Vision-Instruct

Related models

Same family or similar size — useful when shopping around.

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License
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License
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