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MetaFood industry

Llama for the food industry

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 food industry. It's usable for general work, but first look at the options we recommend for food 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 food industry

Core tasks in the food industry
  • Optically inspecting and sorting products by defects, ripeness and internal quality
  • Forecasting shelf life and demand to reduce food waste and shrinkage
  • Developing and reformulating recipes, including nutritional value, allergens and labelling
  • Maintaining HACCP plans, food safety risks and regulations per market
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 businesses therefore may not install the multimodal Llama 4 models themselves under the licence terms. Weigh this heavily before deploying it in the food industry.

Confidentiality and GDPR

GDPR: Caution

In this sector the data is mostly business data (recipes, suppliers, production figures) and rarely personal data, but recipes and specifications are trade secrets. Ask every provider whether your data is used to train models: Trace One excludes training of public models, while OneThird, according to its terms, receives a perpetual licence to anonymised, aggregated data. Pay attention to hosting location: OneThird and Delicious Data host in the EU, SGS FoodNexus is Swiss, and with Qcify the American parent is the controller. Hardly any provider states which AI model sits behind it (Trace One names Gemini). An AI inspection or HACCP proposal does not replace release by a competent employee: legal responsibility for food safety (Regulation (EC) No 178/2002) and labelling (Regulation (EU) No 1169/2011) remains with you. Cameras on the shop floor can also capture employees; arrange that with the works council and a DPIA.

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 food industry

Claude for the food industryAnthropic · editorial 9.01506Gemini for the food industryGoogle · editorial 8.61527ChatGPT for the food industryOpenAI · edition 8.91485Copilot for the food industryMicrosoft · editorial 8.31485
All options for the food industry
Professional tools on Llama

We know of no professional tool for the food industry that runs publicly on Llama.

Questions about Llama for the food industry

Is Llama suitable for the food industry?
Not specifically. Llama isn't on our list for food industry; it's broadly applicable, but first look at the options we recommend for food industry. Keep a professional in the loop for every use.
May I put confidential data into Llama?
In this sector the data is usually business data (recipes, suppliers, production figures) and rarely personal data, but recipes and specifications are trade secrets. Ask every provider whether your data is used to train models: Trace One excludes training of public models, while OneThird, under its terms, receives a perpetual licence to anonymised, aggregated data. Pay attention to hosting location: OneThird and Delicious Data host in the EU, SGS FoodNexus is Swiss, and with Qcify the American parent is the controller. Hardly any provider names which AI model sits behind it (Trace One names Gemini). An AI inspection or HACCP proposal does not replace release by a competent employee: the legal responsibility for food safety (Regulation (EC) No 178/2002) and for labelling (Regulation (EU) No 1169/2011) remains yours. Cameras on the shop floor can also capture employees; arrange that with the works council and a DPIA. 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 28 options for the food industryProfessional tools and general assistants side by side, on GDPR profile, price and quality.

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