What hardware do I need to run Llama 3.2 11B Vision?

At its most compressed (Q4_K_M) it needs roughly 8GB of VRAM, and about 13GB for good quality. VRAM figures are approximate and depend on context length and settings.

Is Llama 3.2 11B Vision free for commercial use?

Commercial use is permitted, but with conditions. Commercial use is permitted, with the same 700 million monthly active user threshold as other recent Llama releases, above which a separate licence from Meta is required. Read the licence before relying on it at scale.

Can I run Llama 3.2 11B Vision on Apple Silicon?

Yes. Llama 3.2 11B Vision has builds optimised for Apple Silicon, through MLX or GGUF on a Mac.

Does Llama 3.2 11B Vision run on CPU?

Yes, Llama 3.2 11B Vision can run on the CPU, though generation is slower than on a GPU.

What is Llama 3.2 11B Vision's context window?

Llama 3.2 11B Vision has a context window of 131,072 tokens, about 131k.

Llama 3.2 11B Vision

Name: Llama 3.2 11B Vision
Author: Meta

Meta · Vision-language · 11B · 131k context · Released 25 September 2024

Permitted with conditions Text + ImageText Open weights Runs on CPU Apple Silicon

Meta's 11-billion-parameter vision-language model, a solid general choice for understanding images alongside text on a mid-range card. Well supported across local tooling, with a long 128k context window.

Strengths

Capable general image-and-text understanding on 12GB to 16GB cards
Broad local tooling support, including Ollama
Long 128k context window

Weaknesses

Weaker at dense OCR and documents than Qwen2.5-VL of similar size
The Llama licence carries conditions, unlike Apache 2.0 models
Needs 12GB or more for usable quality

Hardware requirements

Quantisation	Approx. VRAM	Notes
Q4_K_M	~8GB	Fits a 12GB card with short context, including the vision encoder
Q8_0	~13GB	A good fit for a 16GB card
FP16	~22GB	Full precision, needs 24GB

Also runs on CPU (slower). Optimised builds available for Apple Silicon.

What you'd need to run this

Roughly what a machine to run this would need, at up to three levels of quality. Memory is the deciding factor.

Minimum to run it

Q4_K_M · ~8GB needed

One 12GB GPU

NVIDIA GeForce RTX 3060 12GB

or a Mac or mini-PC with unified memory, if you prefer no discrete GPU, Mac mini M5 Pro .

At least 32GB of system RAM alongside the card.

around £700–£1,100

What else 12GB runs →

For good quality

Q8_0 · ~13GB needed

One 24GB GPU

NVIDIA Tesla P40

or a Mac or mini-PC with unified memory, if you prefer no discrete GPU, Mac mini M5 Pro .

32–64GB of system RAM alongside the card.

around £700–£1,100

What else 24GB runs →

Best quality

FP16 · ~22GB needed

One 32GB GPU

NVIDIA GeForce RTX 5090

or a Mac or mini-PC with unified memory, if you prefer no discrete GPU, Mac mini M4 Pro .

64GB of system RAM alongside the card.

around £4,000–£8,000

See the Single-card flagship build What else 32GB runs →

Licence

Llama 3.2 Community License — read the licence

Benchmarks

Benchmark	Score	Source	As of
MMMU (val)	50.7	Meta Llama 3.2 Vision model card (CoT, micro-avg)	September 2024
DocVQA (test)	88.4	Meta Llama 3.2 Vision model card (ANLS, test)	September 2024

How it compares

How this model’s reported scores sit against other models we cover, on the same benchmarks. This model is highlighted.

DocVQA (test)

higher is better

Qwen2.5-VL 7B 95.7

Qwen2.5-VL technical report (ANLS, test) · February 2025
Llama 3.2 11B Vision 88.4

Meta Llama 3.2 Vision model card (ANLS, test) · September 2024

MMMU (val)

higher is better

Qwen2.5-VL 7B 58.6

Qwen2.5-VL technical report · February 2025
Llama 3.2 11B Vision 50.7

Meta Llama 3.2 Vision model card (CoT, micro-avg) · September 2024

Llama 3.2 11B Vision: common questions

What hardware do I need to run Llama 3.2 11B Vision?: At its most compressed (Q4_K_M) it needs roughly 8GB of VRAM, and about 13GB for good quality. VRAM figures are approximate and depend on context length and settings.
Is Llama 3.2 11B Vision free for commercial use?: Commercial use is permitted, but with conditions. Commercial use is permitted, with the same 700 million monthly active user threshold as other recent Llama releases, above which a separate licence from Meta is required. Read the licence before relying on it at scale.
Can I run Llama 3.2 11B Vision on Apple Silicon?: Yes. Llama 3.2 11B Vision has builds optimised for Apple Silicon, through MLX or GGUF on a Mac.
Does Llama 3.2 11B Vision run on CPU?: Yes, Llama 3.2 11B Vision can run on the CPU, though generation is slower than on a GPU.
What is Llama 3.2 11B Vision's context window?: Llama 3.2 11B Vision has a context window of 131,072 tokens, about 131k.

Availability

Official page
Hugging Face
ollama run llama3.2-vision:11b

Where to get quantised weights

Some of the best quantised weights are made by the community, not the model’s authors. Look this model up on these providers:

Bartowski GGUF Q2-Q8 (imatrix)
Vision support in llama.cpp is limited, so check your runtime handles the image encoder.
mradermacher
Very broad coverage of models, in both static and imatrix GGUF.

Recommended for

General image understanding on a 12GB to 16GB card
Users already in the Llama ecosystem who want vision
A well-supported starting point for local multimodal work

Related models

Qwen2.5-VL 7B

Run it with

Ollama

Glossary

Context window

Our coverage

Meta releases Muse Glimmer, a 30B open model under Apache 2.0 built to run on one GPU

Catalogue entry last verified 30 July 2026. Specifications change; verify anything you are about to spend money on.