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Run Llama 3.3 70B in the EU through an OpenAI-compatible API

Llama 3.3 70B Instruct is Meta's 70-billion-parameter text model, released in December 2024 and still one of the most widely deployed open models. On inference.eu you call it with the OpenAI or Anthropic request format, your requests are processed in EU data centres, and nothing you send is used for training.

Contact salesExample request
  1. 0170B
  2. 02EU data centres
  3. 03Llama 3.3 Community License

What Llama 3.3 70B is

Llama 3.3 70B Instruct is a dense, text-only language model from Meta with 70 billion parameters and a context window of 128K tokens. It is an instruction-tuned model, built on Llama 3.1 70B, and Meta lists English, German, French, Italian, Portuguese, Spanish, Hindi and Thai as supported languages.

Because it is dense rather than a mixture of experts, every token passes through all 70 billion parameters. That makes its behaviour predictable and well understood: it has been tested by thousands of teams since its release, and most frameworks, prompt libraries and evaluation tools support it out of the box.

What it does well, and where it falls short

Llama 3.3 70B is a solid all-rounder for chat, summarisation, classification, extraction and drafting in the major Western European languages. It follows system prompts reliably, supports tool calling and produces consistent JSON when you ask for it, which is why many teams use it as the default model behind internal assistants.

It is no longer the strongest open model. Newer releases such as Qwen3, Gemma 4 or Mistral Small 4 reason better, write better code and accept images, which Llama 3.3 does not. It has no separate thinking mode, so multi-step maths and complex agent tasks are better served by a reasoning model. Choose it when you want a proven, stable baseline.

Calling Llama 3.3 70B through the API

inference.eu speaks the OpenAI request format, so the official OpenAI SDKs for Python and JavaScript, LangChain, LlamaIndex and the Vercel AI SDK work unchanged. Set the base URL to the inference.eu API, use your inference.eu key, and set the model to llama-3.3-70b-instruct.

Chat completions, streaming, tool calls and JSON mode work as you would expect. If your code uses the Anthropic Messages format instead, the same model is available there too, so tools built for Claude can switch to Llama 3.3 without a rewrite. Your prompts, few-shot examples and output parsing stay exactly as they are.

Data residency for Llama 3.3 70B

When you call Llama 3.3 70B on inference.eu, your prompts and the model's responses are processed in data centres in the European Union. They are used to answer your request and are never used to train any model.

We sign a data processing agreement under Article 28 of the GDPR with every customer and provide our list of subprocessors, so your data protection officer can see exactly who handles the data and where. Billing is in euros. Note that the Llama 3.3 Community License has its own terms, including an acceptable use policy and an attribution requirement, which apply to how you use the model.

llama-3.3-70b-instruct · Python
import os
from openai import OpenAI

client = OpenAI(base_url="https://api.inference.eu/v1", api_key=os.environ["INFERENCE_EU_API_KEY"])

response = client.chat.completions.create(
    model="llama-3.3-70b-instruct",
    messages=[{"role": "user", "content": "Summarise this contract in five bullet points."}],
)
print(response.choices[0].message.content)

What teams use it for

  • 1

    Internal assistants

    A dependable default for company chat assistants that answer questions, rewrite text and summarise documents in English, German, French, Italian and Spanish.

  • 2

    Structured extraction

    Pull names, dates, amounts and clauses out of emails, invoices and contracts into JSON that your systems can process.

  • 3

    Baseline for migrations

    A well-known reference model when you move a workload from a US provider and want to compare quality model by model.

Llama 3.3 70B Instruct: common questions

The questions buyers, developers and legal teams ask us most. Something missing? Ask us directly.

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