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Llama 3.1 70B

Llama 3.1 70B is Meta's pretrained base checkpoint with 128K context, December 2023 cutoff and Llama 3.1 Community License.

Foundation ModelText Open Source
In plain English

What is this model and why does it matter?

Llama 3.1 70B is Meta's pretrained base model with 128K context and a December 2023 knowledge cutoff.

Fine-tuningResearchDomain adaptationSynthetic data
Model overview

Llama 3.1 70B: features, use cases and important details

Llama 3.1 70B is a pretrained base checkpoint from Meta’s July 2024 Llama 3.1 family.

Verified model facts

Meta documents 128K context, eight officially supported languages and a December 2023 pretraining cutoff.

Best fit

This base model is most appropriate for research, fine-tuning, domain adaptation and model-development work rather than direct assistant use.

Limitations

It is not instruction tuned, can produce unreliable outputs without post-training, and hardware needs increase sharply with parameter count.

Get started

How to use this model

  1. Accept the Llama 3.1 Community License.
  2. Download the official 70B base checkpoint.
  3. Provision suitable inference or training hardware.
  4. Use it as a pretrained foundation rather than assuming chat alignment.
  5. Fine-tune or adapt it for the intended task and evaluate carefully.
Copy and try

Example prompts

  • Continue this technical corpus in the same style.
  • Use this checkpoint as the base for domain fine-tuning.
  • Evaluate perplexity on this research dataset.
Capabilities

What it can do

  • Base language modeling
  • 128K context
  • Multilingual text
  • Fine-tuning foundation
Best for

Practical use cases

  • Research
  • Fine-tuning
  • Domain adaptation
  • Model experimentation
Pricing

What does it cost?

Pretrained open-weight checkpoint under the Llama 3.1 Community License; no direct Meta token price applies.

Simple summarySelf-hosting cost scales sharply with the 70B parameter size. This is a base checkpoint rather than a managed Meta API.

What stands out

  • Official Meta base weights
  • 128K context
  • 70B size supports different capability/infrastructure tradeoffs

Things to consider

  • Not instruction-tuned for chat
  • Custom license
  • December 2023 static cutoff
Limitations

Important restrictions and trade-offs

  • Base model should not be confused with an assistant
  • Requires post-training for many end-user applications
  • Can generate inaccurate content
SimplifyAITools verdict

Our editorial take

Use Llama 3.1 70B primarily as a pretrained foundation for research or adaptation; choose an Instruct checkpoint for ready-to-use conversational behavior.

References

Primary sources

  1. Open source 1 ↗
  2. Open source 2 ↗
  3. Open source 3 ↗
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