Can I run Llama 3.3 70B locally?

Yes, the weights are open and hosted on Hugging Face under meta-llama/Llama-3.3-70B-Instruct. Tools like Ollama and LM Studio can run quantised versions, though 70B is demanding — expect to need 40 GB or more of VRAM or RAM depending on the quantisation level.

What does it cost via API?

Pricing on the facts line is $0.59 per million input tokens and $0.79 per million output tokens, which is low for a model of this capability class.

How does this compare to smaller Llama 3 models?

Meta positions 3.3 70B as outperforming smaller variants on common benchmarks while still being runnable on consumer hardware with quantisation; if you need something lighter and faster, the 8B Instruct is the obvious step down, at the cost of quality on harder tasks.

Llama 3.3 70B Instruct

5314°

#llm #meta-llama #chat #multilingual #writing #local

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Guides for this model

How to Install Ollama and Run a Local AI (Windows, Mac, Linux)

Ollama vs LM Studio (2026): which local AI app to use, and which top models each one runs

Best local LLM by use case (October 2026): the right open model for every job

How much VRAM do I actually need for local AI?

What is a GGUF file? Quantized models explained (Q4, Q8, fp8, NF4)

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Meta | 131,072 token context | $0.10/M input, $0.32/M output. The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out). The Llama 3.3 instruction tuned text only model is optimized for multilingual dialogue use cases and outperforms many of the available open source and closed chat models on common industry benchmarks. Supported languages: English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai. Model CardOpens in new tab

Captain's notes

Written by Captain, the house editor

Notes from 2026-10-13

Llama 3.3 70B Instruct is Meta's instruction-tuned, text-in/text-out model at the 70B scale, with open weights you can download and run yourself. It targets multilingual dialogue across eight languages and, according to Meta, beats many open and closed chat models on standard benchmarks at this size. At under a dollar per million tokens via API, it sits in a useful middle ground between small fast models and expensive frontier ones.

Known for

Strong multilingual chat across English, German, French, Italian, Portuguese, Hindi, Spanish and Thai
Open weights: download, self-host or quantise as you like
Competitive instruction-following at the 70B class without frontier pricing
128k token context window covers most long-document tasks

Watch out for

Text only — no image, audio or video input despite the broader Llama 3 family supporting multimodal variants
70B is heavy; you will need substantial VRAM or CPU RAM to run it locally at full precision
Meta's licence permits broad use but does carry usage restrictions; check it before commercial deployment

Best for

Prompts to try

Multilingual customer reply

A customer wrote to us in Spanish: 'Hola, compré el producto hace dos semanas y aún no ha llegado. ¿Pueden ayudarme?' Draft a professional, empathetic reply in Spanish, then provide an English summary of what you said for our internal records.

Summarise and translate

Here is a paragraph of German text: 'Die Bundesregierung hat heute ein neues Klimaschutzpaket vorgestellt, das bis 2035 eine Reduzierung der CO2-Emissionen um 70 Prozent vorsieht.' Summarise the key point in one sentence, then translate the full paragraph into Hindi.

Rewrite for clarity

Rewrite the following legal boilerplate in plain English that a non-lawyer can understand in under 30 seconds: 'The indemnifying party shall defend, indemnify and hold harmless the indemnified party from and against any and all claims, damages, losses, costs and expenses arising out of or relating to any breach of this Agreement.'

Compare with

Llama 3.2 3B Instruct
Open-weights model
131,072 token context · $0.05/M input, $0.33/M output
Llama 3.1 70B Instruct
Open-weights model
131,072 token context · $0.40/M input, $0.40/M output
Llama 3.3 70B Instruct Turbo
Open-weights model
131,072 token context · $0.10/M input, $0.32/M output
Llama 3.2 1B Instruct
Open-weights model
60,000 token context · $0.03/M input, $0.20/M output

More text models from meta-llama

Questions people ask

Can I run Llama 3.3 70B locally?: Yes, the weights are open and hosted on Hugging Face under meta-llama/Llama-3.3-70B-Instruct. Tools like Ollama and LM Studio can run quantised versions, though 70B is demanding — expect to need 40 GB or more of VRAM or RAM depending on the quantisation level.
What does it cost via API?: Pricing on the facts line is $0.59 per million input tokens and $0.79 per million output tokens, which is low for a model of this capability class.
How does this compare to smaller Llama 3 models?: Meta positions 3.3 70B as outperforming smaller variants on common benchmarks while still being runnable on consumer hardware with quantisation; if you need something lighter and faster, the 8B Instruct is the obvious step down, at the cost of quality on harder tasks.

Captain's verdict
A genuinely capable open-weights chat model at a price and size that makes it hard to argue against for multilingual work.

Model card on Hugging Face

Captain writes these notes from the model's own description and model card. Prices and context sizes are the provider's at the time of writing and can change.

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Updated Oct 22, 2026

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Typical model: The middle of the catalog: half the models with a figure grew faster over the period, half slower.

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Llama 3.3 70B Instruct is a text model for the Text / LLM family listed on ModelTrends.ai, a read-only catalog of open source AI image, video and text models. Compare it with other Text / LLM models, check its heat score to see how it is trending, and open it on PirateDiffusion or BitVector to try it.

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