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MetaPharmaceutical industry

Llama for pharmaceutical industry

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

Not specifically recommended

Llama is not on our list for the pharmaceutical industry. Usable for general work, but first look at the options we recommend for the pharmaceutical industry.

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 the pharmaceutical industry

Core tasks in the pharmaceutical industry
  • Finding and optimising targets, proteins and candidate molecules with AI models
  • Setting up clinical studies: recruiting patients, recording source data and monitoring data quality
  • Drafting regulatory documents (protocols, CSRs, dossiers) with traceable sources
  • Processing adverse event reports, coding them and detecting safety signals
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 specific GDPR concern. The Llama 4 Acceptable Use Policy prohibits the multimodal models for businesses headquartered in the EU. Dutch companies therefore may not install the multimodal Llama 4 models themselves under the licence terms. Weigh this heavily before using it in the pharmaceutical industry.

Confidentiality and GDPR

GDPR: Caution

This sector involves health data of trial participants and patients (special category personal data under Article 9 GDPR) and confidential research data. Ask every provider where the data is stored and whether it is used to train models: Castor hosts in the Netherlands (Google Cloud europe-west4) and does not share data or models between customers, Cradle states that source data never goes to third-party AI models, Iris.ai hosts on AWS in Ireland and Germany. Biolevate and Ennov also run in private cloud or on-premises. With Veeva Vault AI and Yseop, texts go to Anthropic models via Amazon Bedrock; check the region and the data processing agreement. If you work in GxP processes, an AI tool must also be validated (EU GMP Annex 11) and a competent employee remains responsible. For AI in medicines development, the EMA has a reflection paper (2024) and is working with the FDA on joint principles.

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 the pharmaceutical industry

Claude for the pharmaceutical industryAnthropic · editorial 9.01506Gemini for the pharmaceutical industryGoogle · editorial 8.61526ChatGPT for the pharmaceutical industryOpenAI · edition 8.91485Copilot for the pharmaceutical industryMicrosoft · editorial 8.31485
All options for the pharmaceutical industry
Professional tools on Llama

We do not know of a professional tool for the pharmaceutical industry that publicly runs on Llama.

Questions about Llama for the pharmaceutical industry

Is Llama suitable for the pharmaceutical industry?
Not specifically. Llama is not on our list for the pharmaceutical industry; it is broadly usable, but first look at the options we recommend for the pharmaceutical industry. Keep a professional in the loop for every use.
May I put confidential data into Llama?
This sector involves health data from trial participants and patients (special category personal data under Article 9 GDPR) and confidential research data. Ask every provider where the data is stored and whether it is used to train models: Castor hosts in the Netherlands (Google Cloud europe-west4) and does not share data or models between customers, Cradle states that source data never reaches third-party AI models, and Iris.ai hosts on AWS in Ireland and Germany. Biolevate and Ennov also run in private cloud or on-premises. With Veeva Vault AI and Yseop, text goes to Anthropic models via Amazon Bedrock, so check the region and the data processing agreement. If you work in GxP processes, an AI tool must also be validated (EU GMP Annex 11) and a competent staff member remains responsible. For AI in drug development, the EMA has a reflection paper (2024) and is working with the FDA on joint principles. 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 25 options for pharmaceutical industryProfessional tools and general assistants side by side, on GDPR profile, price and quality.

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