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Llama 4 is Meta’s first natively multimodal, mixture-of-experts open-weight generation. Both variants run 17 billion active parameters and accept multilingual text and images, producing multilingual text and code.
Available in Ollang Workflows as llama — Document Translation and Subtitle Translation. See the Translation catalog.
Llama 4 does not serve AI Dubbing Orders. Select a different provider for the translate step of a dubbing Workflow.

Models

Knowledge cutoff for both is August 2024 — the oldest in this catalog, which matters for content containing recent product names, terminology, or events.

Supported languages

Meta officially supports 12 languages: Arabic, English, French, German, Hindi, Indonesian, Italian, Portuguese, Spanish, Tagalog, Thai, and Vietnamese. This is the single most important constraint to design around. Outside those 12, quality falls off sharply compared with the 100+ language providers.

Key capabilities

  • Extreme context length — Scout’s 10M-token window is by a wide margin the largest here, enough for entire books, full documentation sets, or complete season subtitle runs in a single pass.
  • Native multimodality for documents combining text and images.
  • Open weights, relevant for organizations running parallel self-hosted evaluation or fine-tuning for domain-specific glossaries.

Where it fits in a workflow

Llama 4 is the right choice for high-volume work inside its 12 supported languages — bulk subtitle backlogs, internal documentation, and draft passes destined for human review. For the same content in an unsupported language, Agentic Turbo or DeepL will produce better output.

Trade-offs

  • Narrow official language coverage — 12 languages.
  • Oldest knowledge cutoff in the catalog at August 2024.
  • No AI Dubbing support.
  • Draft-grade rather than deliverable-grade on nuance-heavy content; budget for review.

Reference