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MetaResearch & science

Llama for research & science

Meta's natively multimodal, open-weight Mixture-of-Experts family (Scout and Maverick), free to download and self-host.

Not specifically recommended

Llama isn't on our list for research & science. It's usable for general work, but first look at the options we recommend for research & science.

GDPR profileOur summary of what the provider itself publishes about your data: EU hosting possible, no training on your data for business use, and self-hosting available. Caution applies to a model with a documented problem, such as an investigation by a regulator. How we measure
GDPR: Caution
QualityQuality from blind duels on LMArena: users choose between two anonymous answers. A difference of about 20 points is noticeable, a few points is noise. How we measure
–Elo, independent
Editorial scoreOur own assessment on 10 of suitability for professional work, price and privacy. This is a judgement, not a measurement; that is why it always sits alongside the Elo. How we measure
7,6
Entry price
Free
Full GDPR check

What Llama does in research & science

Core tasks in research & science
  • Literature search and exploration with semantic search and citation networks
  • Screening titles, abstracts and full texts for systematic reviews
  • Extracting and summarising data and study characteristics from papers
  • Writing and editing manuscripts, abstracts and research proposals
Where Llama is strong
  • Open weights, fully self-hostable
  • Fine-tunable on your own data
  • Very large context window (Scout 10M)
  • GPU-efficient (Mixture-of-Experts)

Llama has a concrete GDPR concern. The Llama 4 Acceptable Use Policy prohibits the multimodal models for businesses headquartered in the EU. Dutch companies therefore may not, under the licence, install the multimodal Llama 4 models themselves. Weigh this heavily before using it in research & science.

Confidentiality and GDPR

GDPR: Caution

Never use AI as a source: every reference must be traceable to the original article, as fabricated or wrongly attributed citations are the most common error. Unpublished data, research proposals and peer-review manuscripts are confidential or commercially sensitive, so do not enter them into a consumer account without a data processing agreement, and check whether the provider stores your input or uses it for training (publishers usually prohibit this explicitly for peer review). If you work with personal data from research participants, the GDPR and your own ethics review apply: running models locally or using an EU-hosted tool with data minimisation is then the safe route. Finally, document your search strategy and your AI use: journals and funders increasingly ask for this, and a review must remain reproducible.

Self-hosting gives full data control within your own EU infrastructure, a strong GDPR argument.

Rule of thumb Use the business variant with a data processing agreement, and keep a human in the loop for decisions that matter.
Caution the Llama 4 Acceptable Use Policy prohibits the multimodal models for businesses headquartered in the EU. Dutch businesses therefore may not install the multimodal Llama 4 models themselves under the licence terms.

Prices

Self-hostingFreeOpen weights; infrastructure costs only
Meta AI$0Free in WhatsApp/Instagram/Messenger
Hosted API (third parties)from ~$0.03 / 1M inVia Bedrock, Azure, Together, Groq, Novita, varies widely by provider and model size; Meta's own Llama API retired July 2026

Other models for research & science

Claude for research & scienceAnthropic · editorial 9.01506Gemini for research & scienceGoogle · editorial 8.61527ChatGPT for research & scienceOpenAI · edition 8.91485Le Chat (Mistral) for research & scienceMistral AI · editorial 8.41426
All options for research & science
Professional tools on Llama

We don't know of a professional tool for research & science that runs publicly on Llama.

Questions about Llama for research & science

Is Llama suitable for research & science?
Not specifically. Llama isn't on our list for research & science; it's broadly usable, but first look at the options we recommend for research & science. Keep a professional in the loop for every use.
May I put confidential data into Llama?
Never use AI as a source: every reference must be traceable to the original article, as fabricated or misattributed citations are the most common error. Unpublished data, research proposals and peer-review manuscripts are confidential or commercially sensitive, don't enter them into a consumer account without a data processing agreement, and check whether the provider stores your input or uses it for training (in peer review, publishers usually prohibit this explicitly). If you work with personal data of research participants, the GDPR and your own ethics review apply: running locally or using an EU-hosted tool with data minimisation is then the safe route. Finally, record your search strategy and your AI use: journals and funders increasingly ask for this, and a review must remain reproducible. Self-hosting gives full data control within your own EU infrastructure, a strong GDPR argument.
What does Llama cost?
There is self-hosting (free), Meta AI ($0), Hosted API (third parties) (from ~$0.03 / 1M in). Check current prices on the official site.
Next stepAll 30 options for research & scienceProfessional tools and general assistants side by side, on GDPR profile, price and quality.

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